Report

Dataset statistics

Number of variables	122
Number of observations	10
Missing cells	406
Missing cells (%)	33.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	17.7 KiB
Average record size in memory	1.8 KiB

Variable types

Numeric	14
Categorical	105
Boolean	3

Warnings

`NAME_HOUSING_TYPE` has constant value "House / apartment"	Constant
`FLAG_MOBIL` has constant value "1"	Constant
`FLAG_CONT_MOBILE` has constant value "1"	Constant
`FLAG_EMAIL` has constant value "0"	Constant
`REG_REGION_NOT_LIVE_REGION` has constant value "0"	Constant
`REG_REGION_NOT_WORK_REGION` has constant value "0"	Constant
`LIVE_REGION_NOT_WORK_REGION` has constant value "0"	Constant
`REG_CITY_NOT_LIVE_CITY` has constant value "0"	Constant
`NONLIVINGAPARTMENTS_MODE` has constant value "0.0"	Constant
`NONLIVINGAREA_MODE` has constant value "0.0"	Constant
`FONDKAPREMONT_MODE` has constant value "reg oper account"	Constant
`HOUSETYPE_MODE` has constant value "block of flats"	Constant
`EMERGENCYSTATE_MODE` has constant value "False"	Constant
`FLAG_DOCUMENT_2` has constant value "0"	Constant
`FLAG_DOCUMENT_4` has constant value "0"	Constant
`FLAG_DOCUMENT_5` has constant value "0"	Constant
`FLAG_DOCUMENT_6` has constant value "0"	Constant
`FLAG_DOCUMENT_7` has constant value "0"	Constant
`FLAG_DOCUMENT_9` has constant value "0"	Constant
`FLAG_DOCUMENT_10` has constant value "0"	Constant
`FLAG_DOCUMENT_11` has constant value "0"	Constant
`FLAG_DOCUMENT_12` has constant value "0"	Constant
`FLAG_DOCUMENT_13` has constant value "0"	Constant
`FLAG_DOCUMENT_15` has constant value "0"	Constant
`FLAG_DOCUMENT_16` has constant value "0"	Constant
`FLAG_DOCUMENT_17` has constant value "0"	Constant
`FLAG_DOCUMENT_18` has constant value "0"	Constant
`FLAG_DOCUMENT_19` has constant value "0"	Constant
`FLAG_DOCUMENT_20` has constant value "0"	Constant
`FLAG_DOCUMENT_21` has constant value "0"	Constant
`AMT_REQ_CREDIT_BUREAU_HOUR` has constant value "0.0"	Constant
`AMT_REQ_CREDIT_BUREAU_DAY` has constant value "0.0"	Constant
`AMT_REQ_CREDIT_BUREAU_WEEK` has constant value "0.0"	Constant
`SK_ID_CURR` is highly correlated with `TARGET` and 48 other fields	High correlation
`TARGET` is highly correlated with `SK_ID_CURR` and 46 other fields	High correlation
`CNT_CHILDREN` is highly correlated with `AMT_CREDIT` and 8 other fields	High correlation
`AMT_INCOME_TOTAL` is highly correlated with `AMT_CREDIT` and 48 other fields	High correlation
`AMT_CREDIT` is highly correlated with `CNT_CHILDREN` and 49 other fields	High correlation
`AMT_ANNUITY` is highly correlated with `AMT_INCOME_TOTAL` and 47 other fields	High correlation
`AMT_GOODS_PRICE` is highly correlated with `AMT_INCOME_TOTAL` and 46 other fields	High correlation
`REGION_POPULATION_RELATIVE` is highly correlated with `CNT_CHILDREN` and 49 other fields	High correlation
`DAYS_BIRTH` is highly correlated with `TARGET` and 47 other fields	High correlation
`DAYS_EMPLOYED` is highly correlated with `FLAG_EMP_PHONE` and 43 other fields	High correlation
`DAYS_REGISTRATION` is highly correlated with `SK_ID_CURR` and 44 other fields	High correlation
`DAYS_ID_PUBLISH` is highly correlated with `DAYS_REGISTRATION` and 44 other fields	High correlation
`OWN_CAR_AGE` is highly correlated with `SK_ID_CURR` and 16 other fields	High correlation
`FLAG_EMP_PHONE` is highly correlated with `DAYS_EMPLOYED` and 2 other fields	High correlation
`FLAG_PHONE` is highly correlated with `SK_ID_CURR` and 4 other fields	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN` and 52 other fields	High correlation
`REGION_RATING_CLIENT` is highly correlated with `OWN_CAR_AGE` and 44 other fields	High correlation
`REGION_RATING_CLIENT_W_CITY` is highly correlated with `OWN_CAR_AGE` and 44 other fields	High correlation
`HOUR_APPR_PROCESS_START` is highly correlated with `AMT_ANNUITY` and 45 other fields	High correlation
`REG_CITY_NOT_WORK_CITY` is highly correlated with `OWN_CAR_AGE` and 4 other fields	High correlation
`LIVE_CITY_NOT_WORK_CITY` is highly correlated with `OWN_CAR_AGE` and 4 other fields	High correlation
`EXT_SOURCE_1` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`EXT_SOURCE_2` is highly correlated with `DAYS_EMPLOYED` and 43 other fields	High correlation
`EXT_SOURCE_3` is highly correlated with `SK_ID_CURR` and 8 other fields	High correlation
`APARTMENTS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`BASEMENTAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BEGINEXPLUATATION_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BUILD_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`COMMONAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ELEVATORS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ENTRANCES_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMAX_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMIN_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LANDAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAPARTMENTS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAPARTMENTS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`APARTMENTS_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`BASEMENTAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BEGINEXPLUATATION_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BUILD_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`COMMONAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ELEVATORS_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ENTRANCES_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMAX_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMIN_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LANDAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAPARTMENTS_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`APARTMENTS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`BASEMENTAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BEGINEXPLUATATION_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BUILD_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`COMMONAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ELEVATORS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ENTRANCES_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMAX_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMIN_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LANDAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAPARTMENTS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAPARTMENTS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`TOTALAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`OBS_30_CNT_SOCIAL_CIRCLE` is highly correlated with `AMT_INCOME_TOTAL` and 45 other fields	High correlation
`DEF_30_CNT_SOCIAL_CIRCLE` is highly correlated with `SK_ID_CURR` and 46 other fields	High correlation
`OBS_60_CNT_SOCIAL_CIRCLE` is highly correlated with `AMT_INCOME_TOTAL` and 45 other fields	High correlation
`DEF_60_CNT_SOCIAL_CIRCLE` is highly correlated with `SK_ID_CURR` and 46 other fields	High correlation
`DAYS_LAST_PHONE_CHANGE` is highly correlated with `REGION_POPULATION_RELATIVE` and 44 other fields	High correlation
`FLAG_DOCUMENT_3` is highly correlated with `OWN_CAR_AGE` and 2 other fields	High correlation
`FLAG_DOCUMENT_8` is highly correlated with `CNT_CHILDREN` and 5 other fields	High correlation
`FLAG_DOCUMENT_14` is highly correlated with `CNT_CHILDREN` and 8 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_MON` is highly correlated with `CNT_CHILDREN` and 9 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_QRT` is highly correlated with `CNT_CHILDREN` and 9 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_YEAR` is highly correlated with `CNT_CHILDREN` and 50 other fields	High correlation
`SK_ID_CURR` is highly correlated with `TARGET` and 48 other fields	High correlation
`TARGET` is highly correlated with `SK_ID_CURR` and 46 other fields	High correlation
`CNT_CHILDREN` is highly correlated with `AMT_CREDIT` and 8 other fields	High correlation
`AMT_INCOME_TOTAL` is highly correlated with `AMT_CREDIT` and 49 other fields	High correlation
`AMT_CREDIT` is highly correlated with `CNT_CHILDREN` and 49 other fields	High correlation
`AMT_ANNUITY` is highly correlated with `AMT_INCOME_TOTAL` and 48 other fields	High correlation
`AMT_GOODS_PRICE` is highly correlated with `AMT_INCOME_TOTAL` and 46 other fields	High correlation
`REGION_POPULATION_RELATIVE` is highly correlated with `OWN_CAR_AGE` and 45 other fields	High correlation
`DAYS_BIRTH` is highly correlated with `TARGET` and 50 other fields	High correlation
`DAYS_EMPLOYED` is highly correlated with `CNT_CHILDREN` and 49 other fields	High correlation
`DAYS_REGISTRATION` is highly correlated with `SK_ID_CURR` and 45 other fields	High correlation
`DAYS_ID_PUBLISH` is highly correlated with `SK_ID_CURR` and 49 other fields	High correlation
`OWN_CAR_AGE` is highly correlated with `SK_ID_CURR` and 22 other fields	High correlation
`FLAG_EMP_PHONE` is highly correlated with `DAYS_BIRTH` and 4 other fields	High correlation
`FLAG_PHONE` is highly correlated with `SK_ID_CURR` and 6 other fields	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN` and 52 other fields	High correlation
`REGION_RATING_CLIENT` is highly correlated with `OWN_CAR_AGE` and 44 other fields	High correlation
`REGION_RATING_CLIENT_W_CITY` is highly correlated with `OWN_CAR_AGE` and 44 other fields	High correlation
`HOUR_APPR_PROCESS_START` is highly correlated with `AMT_ANNUITY` and 45 other fields	High correlation
`REG_CITY_NOT_WORK_CITY` is highly correlated with `OWN_CAR_AGE` and 5 other fields	High correlation
`LIVE_CITY_NOT_WORK_CITY` is highly correlated with `OWN_CAR_AGE` and 5 other fields	High correlation
`EXT_SOURCE_1` is highly correlated with `SK_ID_CURR` and 60 other fields	High correlation
`EXT_SOURCE_2` is highly correlated with `DAYS_EMPLOYED` and 44 other fields	High correlation
`EXT_SOURCE_3` is highly correlated with `TARGET` and 13 other fields	High correlation
`APARTMENTS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`BASEMENTAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BEGINEXPLUATATION_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BUILD_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`COMMONAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ELEVATORS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ENTRANCES_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMAX_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMIN_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LANDAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAPARTMENTS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAPARTMENTS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`APARTMENTS_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`BASEMENTAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BEGINEXPLUATATION_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BUILD_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`COMMONAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ELEVATORS_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ENTRANCES_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMAX_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMIN_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LANDAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAPARTMENTS_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`APARTMENTS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`BASEMENTAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BEGINEXPLUATATION_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BUILD_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`COMMONAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ELEVATORS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ENTRANCES_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMAX_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMIN_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LANDAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAPARTMENTS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAPARTMENTS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`TOTALAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`OBS_30_CNT_SOCIAL_CIRCLE` is highly correlated with `AMT_INCOME_TOTAL` and 45 other fields	High correlation
`DEF_30_CNT_SOCIAL_CIRCLE` is highly correlated with `SK_ID_CURR` and 46 other fields	High correlation
`OBS_60_CNT_SOCIAL_CIRCLE` is highly correlated with `AMT_INCOME_TOTAL` and 45 other fields	High correlation
`DEF_60_CNT_SOCIAL_CIRCLE` is highly correlated with `SK_ID_CURR` and 46 other fields	High correlation
`DAYS_LAST_PHONE_CHANGE` is highly correlated with `REGION_POPULATION_RELATIVE` and 46 other fields	High correlation
`FLAG_DOCUMENT_3` is highly correlated with `OWN_CAR_AGE` and 2 other fields	High correlation
`FLAG_DOCUMENT_8` is highly correlated with `CNT_CHILDREN` and 6 other fields	High correlation
`FLAG_DOCUMENT_14` is highly correlated with `CNT_CHILDREN` and 8 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_MON` is highly correlated with `CNT_CHILDREN` and 9 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_QRT` is highly correlated with `CNT_CHILDREN` and 10 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_YEAR` is highly correlated with `CNT_CHILDREN` and 49 other fields	High correlation
`SK_ID_CURR` is highly correlated with `DAYS_REGISTRATION` and 44 other fields	High correlation
`TARGET` is highly correlated with `EXT_SOURCE_1` and 44 other fields	High correlation
`CNT_CHILDREN` is highly correlated with `CNT_FAM_MEMBERS` and 6 other fields	High correlation
`AMT_INCOME_TOTAL` is highly correlated with `OWN_CAR_AGE` and 43 other fields	High correlation
`AMT_CREDIT` is highly correlated with `AMT_ANNUITY` and 44 other fields	High correlation
`AMT_ANNUITY` is highly correlated with `AMT_CREDIT` and 46 other fields	High correlation
`AMT_GOODS_PRICE` is highly correlated with `AMT_CREDIT` and 45 other fields	High correlation
`REGION_POPULATION_RELATIVE` is highly correlated with `APARTMENTS_AVG` and 42 other fields	High correlation
`DAYS_BIRTH` is highly correlated with `EXT_SOURCE_3` and 41 other fields	High correlation
`DAYS_EMPLOYED` is highly correlated with `EXT_SOURCE_3` and 43 other fields	High correlation
`DAYS_REGISTRATION` is highly correlated with `SK_ID_CURR` and 44 other fields	High correlation
`DAYS_ID_PUBLISH` is highly correlated with `DAYS_REGISTRATION` and 42 other fields	High correlation
`OWN_CAR_AGE` is highly correlated with `SK_ID_CURR` and 12 other fields	High correlation
`FLAG_EMP_PHONE` is highly correlated with `EXT_SOURCE_3`	High correlation
`FLAG_PHONE` is highly correlated with `SK_ID_CURR` and 5 other fields	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN` and 49 other fields	High correlation
`REGION_RATING_CLIENT` is highly correlated with `OWN_CAR_AGE` and 44 other fields	High correlation
`REGION_RATING_CLIENT_W_CITY` is highly correlated with `OWN_CAR_AGE` and 44 other fields	High correlation
`HOUR_APPR_PROCESS_START` is highly correlated with `AMT_ANNUITY` and 45 other fields	High correlation
`REG_CITY_NOT_WORK_CITY` is highly correlated with `OWN_CAR_AGE` and 5 other fields	High correlation
`LIVE_CITY_NOT_WORK_CITY` is highly correlated with `OWN_CAR_AGE` and 5 other fields	High correlation
`EXT_SOURCE_1` is highly correlated with `SK_ID_CURR` and 58 other fields	High correlation
`EXT_SOURCE_2` is highly correlated with `APARTMENTS_AVG` and 40 other fields	High correlation
`EXT_SOURCE_3` is highly correlated with `TARGET` and 6 other fields	High correlation
`APARTMENTS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`BASEMENTAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BEGINEXPLUATATION_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BUILD_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`COMMONAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ELEVATORS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ENTRANCES_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMAX_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMIN_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LANDAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAPARTMENTS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAPARTMENTS_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAREA_AVG` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`APARTMENTS_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`BASEMENTAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BEGINEXPLUATATION_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BUILD_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`COMMONAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ELEVATORS_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ENTRANCES_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMAX_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMIN_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LANDAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAPARTMENTS_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`APARTMENTS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`BASEMENTAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BEGINEXPLUATATION_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`YEARS_BUILD_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`COMMONAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ELEVATORS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`ENTRANCES_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMAX_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`FLOORSMIN_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LANDAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAPARTMENTS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`LIVINGAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAPARTMENTS_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`NONLIVINGAREA_MEDI` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`TOTALAREA_MODE` is highly correlated with `SK_ID_CURR` and 62 other fields	High correlation
`OBS_30_CNT_SOCIAL_CIRCLE` is highly correlated with `AMT_INCOME_TOTAL` and 44 other fields	High correlation
`DEF_30_CNT_SOCIAL_CIRCLE` is highly correlated with `TARGET` and 44 other fields	High correlation
`OBS_60_CNT_SOCIAL_CIRCLE` is highly correlated with `AMT_INCOME_TOTAL` and 44 other fields	High correlation
`DEF_60_CNT_SOCIAL_CIRCLE` is highly correlated with `TARGET` and 44 other fields	High correlation
`DAYS_LAST_PHONE_CHANGE` is highly correlated with `APARTMENTS_AVG` and 41 other fields	High correlation
`FLAG_DOCUMENT_3` is highly correlated with `OWN_CAR_AGE` and 2 other fields	High correlation
`FLAG_DOCUMENT_8` is highly correlated with `CNT_CHILDREN` and 5 other fields	High correlation
`FLAG_DOCUMENT_14` is highly correlated with `CNT_CHILDREN` and 6 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_MON` is highly correlated with `CNT_CHILDREN` and 6 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_QRT` is highly correlated with `CNT_CHILDREN` and 9 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_YEAR` is highly correlated with `CNT_CHILDREN` and 48 other fields	High correlation
`WEEKDAY_APPR_PROCESS_START` is highly correlated with `AMT_ANNUITY` and 18 other fields	High correlation
`AMT_ANNUITY` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 23 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_YEAR` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 15 other fields	High correlation
`OBS_60_CNT_SOCIAL_CIRCLE` is highly correlated with `NAME_FAMILY_STATUS` and 13 other fields	High correlation
`FLAG_EMP_PHONE` is highly correlated with `AMT_ANNUITY` and 11 other fields	High correlation
`OCCUPATION_TYPE` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 22 other fields	High correlation
`NAME_FAMILY_STATUS` is highly correlated with `AMT_ANNUITY` and 13 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_QRT` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 10 other fields	High correlation
`REGION_RATING_CLIENT` is highly correlated with `OCCUPATION_TYPE` and 12 other fields	High correlation
`NAME_TYPE_SUITE` is highly correlated with `AMT_ANNUITY` and 16 other fields	High correlation
`DAYS_LAST_PHONE_CHANGE` is highly correlated with `AMT_ANNUITY` and 18 other fields	High correlation
`DAYS_BIRTH` is highly correlated with `AMT_ANNUITY` and 27 other fields	High correlation
`FLAG_WORK_PHONE` is highly correlated with `SK_ID_CURR` and 2 other fields	High correlation
`CODE_GENDER` is highly correlated with `AMT_ANNUITY` and 10 other fields	High correlation
`TARGET` is highly correlated with `DAYS_BIRTH` and 7 other fields	High correlation
`HOUR_APPR_PROCESS_START` is highly correlated with `AMT_ANNUITY` and 19 other fields	High correlation
`SK_ID_CURR` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 42 other fields	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 14 other fields	High correlation
`FLAG_DOCUMENT_3` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 8 other fields	High correlation
`AMT_REQ_CREDIT_BUREAU_MON` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 11 other fields	High correlation
`AMT_INCOME_TOTAL` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 27 other fields	High correlation
`NAME_CONTRACT_TYPE` is highly correlated with `AMT_ANNUITY` and 6 other fields	High correlation
`DAYS_EMPLOYED` is highly correlated with `AMT_ANNUITY` and 11 other fields	High correlation
`EXT_SOURCE_3` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 32 other fields	High correlation
`FLAG_OWN_REALTY` is highly correlated with `AMT_ANNUITY` and 12 other fields	High correlation
`DAYS_REGISTRATION` is highly correlated with `AMT_ANNUITY` and 22 other fields	High correlation
`EXT_SOURCE_2` is highly correlated with `AMT_ANNUITY` and 25 other fields	High correlation
`EXT_SOURCE_1` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 40 other fields	High correlation
`DAYS_ID_PUBLISH` is highly correlated with `OBS_60_CNT_SOCIAL_CIRCLE` and 17 other fields	High correlation
`CNT_CHILDREN` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 9 other fields	High correlation
`REGION_POPULATION_RELATIVE` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 16 other fields	High correlation
`FLAG_DOCUMENT_14` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 9 other fields	High correlation
`NAME_INCOME_TYPE` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 24 other fields	High correlation
`FLAG_OWN_CAR` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 7 other fields	High correlation
`DEF_60_CNT_SOCIAL_CIRCLE` is highly correlated with `DAYS_BIRTH` and 7 other fields	High correlation
`REGION_RATING_CLIENT_W_CITY` is highly correlated with `OCCUPATION_TYPE` and 12 other fields	High correlation
`OBS_30_CNT_SOCIAL_CIRCLE` is highly correlated with `OBS_60_CNT_SOCIAL_CIRCLE` and 13 other fields	High correlation
`ORGANIZATION_TYPE` is highly correlated with `AMT_ANNUITY` and 20 other fields	High correlation
`REG_CITY_NOT_WORK_CITY` is highly correlated with `OCCUPATION_TYPE` and 4 other fields	High correlation
`AMT_CREDIT` is highly correlated with `AMT_ANNUITY` and 23 other fields	High correlation
`AMT_GOODS_PRICE` is highly correlated with `AMT_ANNUITY` and 23 other fields	High correlation
`FLAG_PHONE` is highly correlated with `AMT_ANNUITY` and 5 other fields	High correlation
`DEF_30_CNT_SOCIAL_CIRCLE` is highly correlated with `DAYS_BIRTH` and 7 other fields	High correlation
`LIVE_CITY_NOT_WORK_CITY` is highly correlated with `OCCUPATION_TYPE` and 4 other fields	High correlation
`NAME_EDUCATION_TYPE` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 11 other fields	High correlation
`OWN_CAR_AGE` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 32 other fields	High correlation
`FLAG_DOCUMENT_8` is highly correlated with `WEEKDAY_APPR_PROCESS_START` and 6 other fields	High correlation
`OWN_CAR_AGE` has 7 (70.0%) missing values	Missing
`OCCUPATION_TYPE` has 1 (10.0%) missing values	Missing
`EXT_SOURCE_1` has 6 (60.0%) missing values	Missing
`EXT_SOURCE_3` has 4 (40.0%) missing values	Missing
`APARTMENTS_AVG` has 8 (80.0%) missing values	Missing
`BASEMENTAREA_AVG` has 8 (80.0%) missing values	Missing
`YEARS_BEGINEXPLUATATION_AVG` has 8 (80.0%) missing values	Missing
`YEARS_BUILD_AVG` has 8 (80.0%) missing values	Missing
`COMMONAREA_AVG` has 8 (80.0%) missing values	Missing
`ELEVATORS_AVG` has 8 (80.0%) missing values	Missing
`ENTRANCES_AVG` has 8 (80.0%) missing values	Missing
`FLOORSMAX_AVG` has 8 (80.0%) missing values	Missing
`FLOORSMIN_AVG` has 8 (80.0%) missing values	Missing
`LANDAREA_AVG` has 8 (80.0%) missing values	Missing
`LIVINGAPARTMENTS_AVG` has 8 (80.0%) missing values	Missing
`LIVINGAREA_AVG` has 8 (80.0%) missing values	Missing
`NONLIVINGAPARTMENTS_AVG` has 8 (80.0%) missing values	Missing
`NONLIVINGAREA_AVG` has 8 (80.0%) missing values	Missing
`APARTMENTS_MODE` has 8 (80.0%) missing values	Missing
`BASEMENTAREA_MODE` has 8 (80.0%) missing values	Missing
`YEARS_BEGINEXPLUATATION_MODE` has 8 (80.0%) missing values	Missing
`YEARS_BUILD_MODE` has 8 (80.0%) missing values	Missing
`COMMONAREA_MODE` has 8 (80.0%) missing values	Missing
`ELEVATORS_MODE` has 8 (80.0%) missing values	Missing
`ENTRANCES_MODE` has 8 (80.0%) missing values	Missing
`FLOORSMAX_MODE` has 8 (80.0%) missing values	Missing
`FLOORSMIN_MODE` has 8 (80.0%) missing values	Missing
`LANDAREA_MODE` has 8 (80.0%) missing values	Missing
`LIVINGAPARTMENTS_MODE` has 8 (80.0%) missing values	Missing
`LIVINGAREA_MODE` has 8 (80.0%) missing values	Missing
`NONLIVINGAPARTMENTS_MODE` has 8 (80.0%) missing values	Missing
`NONLIVINGAREA_MODE` has 8 (80.0%) missing values	Missing
`APARTMENTS_MEDI` has 8 (80.0%) missing values	Missing
`BASEMENTAREA_MEDI` has 8 (80.0%) missing values	Missing
`YEARS_BEGINEXPLUATATION_MEDI` has 8 (80.0%) missing values	Missing
`YEARS_BUILD_MEDI` has 8 (80.0%) missing values	Missing
`COMMONAREA_MEDI` has 8 (80.0%) missing values	Missing
`ELEVATORS_MEDI` has 8 (80.0%) missing values	Missing
`ENTRANCES_MEDI` has 8 (80.0%) missing values	Missing
`FLOORSMAX_MEDI` has 8 (80.0%) missing values	Missing
`FLOORSMIN_MEDI` has 8 (80.0%) missing values	Missing
`LANDAREA_MEDI` has 8 (80.0%) missing values	Missing
`LIVINGAPARTMENTS_MEDI` has 8 (80.0%) missing values	Missing
`LIVINGAREA_MEDI` has 8 (80.0%) missing values	Missing
`NONLIVINGAPARTMENTS_MEDI` has 8 (80.0%) missing values	Missing
`NONLIVINGAREA_MEDI` has 8 (80.0%) missing values	Missing
`FONDKAPREMONT_MODE` has 8 (80.0%) missing values	Missing
`HOUSETYPE_MODE` has 8 (80.0%) missing values	Missing
`TOTALAREA_MODE` has 8 (80.0%) missing values	Missing
`WALLSMATERIAL_MODE` has 8 (80.0%) missing values	Missing
`EMERGENCYSTATE_MODE` has 8 (80.0%) missing values	Missing
`AMT_REQ_CREDIT_BUREAU_HOUR` has 2 (20.0%) missing values	Missing
`AMT_REQ_CREDIT_BUREAU_DAY` has 2 (20.0%) missing values	Missing
`AMT_REQ_CREDIT_BUREAU_WEEK` has 2 (20.0%) missing values	Missing
`AMT_REQ_CREDIT_BUREAU_MON` has 2 (20.0%) missing values	Missing
`AMT_REQ_CREDIT_BUREAU_QRT` has 2 (20.0%) missing values	Missing
`AMT_REQ_CREDIT_BUREAU_YEAR` has 2 (20.0%) missing values	Missing
`OWN_CAR_AGE` is uniformly distributed	Uniform
`FLAG_PHONE` is uniformly distributed	Uniform
`EXT_SOURCE_1` is uniformly distributed	Uniform
`APARTMENTS_AVG` is uniformly distributed	Uniform
`BASEMENTAREA_AVG` is uniformly distributed	Uniform
`YEARS_BEGINEXPLUATATION_AVG` is uniformly distributed	Uniform
`YEARS_BUILD_AVG` is uniformly distributed	Uniform
`COMMONAREA_AVG` is uniformly distributed	Uniform
`ELEVATORS_AVG` is uniformly distributed	Uniform
`ENTRANCES_AVG` is uniformly distributed	Uniform
`FLOORSMAX_AVG` is uniformly distributed	Uniform
`FLOORSMIN_AVG` is uniformly distributed	Uniform
`LANDAREA_AVG` is uniformly distributed	Uniform
`LIVINGAPARTMENTS_AVG` is uniformly distributed	Uniform
`LIVINGAREA_AVG` is uniformly distributed	Uniform
`NONLIVINGAPARTMENTS_AVG` is uniformly distributed	Uniform
`NONLIVINGAREA_AVG` is uniformly distributed	Uniform
`APARTMENTS_MODE` is uniformly distributed	Uniform
`BASEMENTAREA_MODE` is uniformly distributed	Uniform
`YEARS_BEGINEXPLUATATION_MODE` is uniformly distributed	Uniform
`YEARS_BUILD_MODE` is uniformly distributed	Uniform
`COMMONAREA_MODE` is uniformly distributed	Uniform
`ELEVATORS_MODE` is uniformly distributed	Uniform
`ENTRANCES_MODE` is uniformly distributed	Uniform
`FLOORSMAX_MODE` is uniformly distributed	Uniform
`FLOORSMIN_MODE` is uniformly distributed	Uniform
`LANDAREA_MODE` is uniformly distributed	Uniform
`LIVINGAPARTMENTS_MODE` is uniformly distributed	Uniform
`LIVINGAREA_MODE` is uniformly distributed	Uniform
`APARTMENTS_MEDI` is uniformly distributed	Uniform
`BASEMENTAREA_MEDI` is uniformly distributed	Uniform
`YEARS_BEGINEXPLUATATION_MEDI` is uniformly distributed	Uniform
`YEARS_BUILD_MEDI` is uniformly distributed	Uniform
`COMMONAREA_MEDI` is uniformly distributed	Uniform
`ELEVATORS_MEDI` is uniformly distributed	Uniform
`ENTRANCES_MEDI` is uniformly distributed	Uniform
`FLOORSMAX_MEDI` is uniformly distributed	Uniform
`FLOORSMIN_MEDI` is uniformly distributed	Uniform
`LANDAREA_MEDI` is uniformly distributed	Uniform
`LIVINGAPARTMENTS_MEDI` is uniformly distributed	Uniform
`LIVINGAREA_MEDI` is uniformly distributed	Uniform
`NONLIVINGAPARTMENTS_MEDI` is uniformly distributed	Uniform
`NONLIVINGAREA_MEDI` is uniformly distributed	Uniform
`TOTALAREA_MODE` is uniformly distributed	Uniform
`WALLSMATERIAL_MODE` is uniformly distributed	Uniform
`SK_ID_CURR` has unique values	Unique
`AMT_CREDIT` has unique values	Unique
`AMT_ANNUITY` has unique values	Unique
`AMT_GOODS_PRICE` has unique values	Unique
`DAYS_BIRTH` has unique values	Unique
`DAYS_EMPLOYED` has unique values	Unique
`DAYS_REGISTRATION` has unique values	Unique
`DAYS_ID_PUBLISH` has unique values	Unique
`EXT_SOURCE_2` has unique values	Unique
`DAYS_LAST_PHONE_CHANGE` has unique values	Unique
`DAYS_LAST_PHONE_CHANGE` has 1 (10.0%) zeros	Zeros

Reproduction

Analysis started	2021-09-09 11:59:39.907465
Analysis finished	2021-09-09 12:00:03.522086
Duration	23.61 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

SK_ID_CURR
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	100007.2

Minimum	100002
Maximum	100012
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	208.0 B

Quantile statistics

Minimum	100002
5-th percentile	100002.45
Q1	100004.5
median	100007.5
Q3	100009.75
95-th percentile	100011.55
Maximum	100012
Range	10
Interquartile range (IQR)	5.25

Descriptive statistics

Standard deviation	3.425395354
Coefficient of variation (CV)	3.425148744 × 10^-5
Kurtosis	-1.23046875
Mean	100007.2
Median Absolute Deviation (MAD)	3
Skewness	-0.1915837245
Sum	1000072
Variance	11.73333333
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
100012	1	10.0%
100011	1	10.0%
100010	1	10.0%
100009	1	10.0%
100008	1	10.0%
100007	1	10.0%
100006	1	10.0%
100004	1	10.0%
100003	1	10.0%
100002	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
100002	1	10.0%
100003	1	10.0%
100004	1	10.0%
100006	1	10.0%
100007	1	10.0%
100008	1	10.0%
100009	1	10.0%
100010	1	10.0%
100011	1	10.0%
100012	1	10.0%

Value	Count	Frequency (%)
100012	1	10.0%
100011	1	10.0%
100010	1	10.0%
100009	1	10.0%
100008	1	10.0%
100007	1	10.0%
100006	1	10.0%
100004	1	10.0%
100003	1	10.0%
100002	1	10.0%

TARGET
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	9
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	10.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

NAME_CONTRACT_TYPE
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	808.0 B

Cash loans	8
Revolving loans	2

Length

Max length	15
Median length	10
Mean length	11
Min length	10

Characters and Unicode

Total characters	110
Distinct characters	13
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Cash loans
2nd row	Cash loans
3rd row	Revolving loans
4th row	Cash loans
5th row	Cash loans

Common Values

Value	Count	Frequency (%)
Cash loans	8	80.0%
Revolving loans	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
loans	10	50.0%
cash	8	40.0%
revolving	2	10.0%

Most occurring characters

Value	Count	Frequency (%)
a	18	16.4%
s	18	16.4%
l	12	10.9%
o	12	10.9%
n	12	10.9%
	10	9.1%
C	8	7.3%
h	8	7.3%
v	4	3.6%
R	2	1.8%
Other values (3)	6	5.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	90	81.8%
Uppercase Letter	10	9.1%
Space Separator	10	9.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	18	20.0%
s	18	20.0%
l	12	13.3%
o	12	13.3%
n	12	13.3%
h	8	8.9%
v	4	4.4%
e	2	2.2%
i	2	2.2%
g	2	2.2%

Uppercase Letter

Value	Count	Frequency (%)
C	8	80.0%
R	2	20.0%

Space Separator

Value	Count	Frequency (%)
	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	100	90.9%
Common	10	9.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	18	18.0%
s	18	18.0%
l	12	12.0%
o	12	12.0%
n	12	12.0%
C	8	8.0%
h	8	8.0%
v	4	4.0%
R	2	2.0%
e	2	2.0%
Other values (2)	4	4.0%

Common

Value	Count	Frequency (%)
	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	110	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	18	16.4%
s	18	16.4%
l	12	10.9%
o	12	10.9%
n	12	10.9%
	10	9.1%
C	8	7.3%
h	8	7.3%
v	4	3.6%
R	2	1.8%
Other values (3)	6	5.5%

CODE_GENDER
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

M	6
F	4

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	M
2nd row	F
3rd row	M
4th row	F
5th row	M

Common Values

Value	Count	Frequency (%)
M	6	60.0%
F	4	40.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
m	6	60.0%
f	4	40.0%

Most occurring characters

Value	Count	Frequency (%)
M	6	60.0%
F	4	40.0%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	10	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
M	6	60.0%
F	4	40.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	10	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
M	6	60.0%
F	4	40.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
M	6	60.0%
F	4	40.0%

FLAG_OWN_CAR
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	138.0 B

False	7
True	3

Common Values
Chart

Value	Count	Frequency (%)
False	7	70.0%
True	3	30.0%

FLAG_OWN_REALTY
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	138.0 B

True	9
False	1

Common Values
Chart

Value	Count	Frequency (%)
True	9	90.0%
False	1	10.0%

CNT_CHILDREN
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	9
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	10.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

AMT_INCOME_TOTAL
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	90.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	167400

Minimum	67500
Maximum	360000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	208.0 B

Quantile statistics

Minimum	67500
5-th percentile	81675
Q1	114750
median	135000
Q3	194625
95-th percentile	319500
Maximum	360000
Range	292500
Interquartile range (IQR)	79875

Descriptive statistics

Standard deviation	88660.02481
Coefficient of variation (CV)	0.5296297779
Kurtosis	1.402619048
Mean	167400
Median Absolute Deviation (MAD)	36000
Skewness	1.319409462
Sum	1674000
Variance	7860600000
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
135000	2	20.0%
270000	1	10.0%
67500	1	10.0%
99000	1	10.0%
112500	1	10.0%
121500	1	10.0%
360000	1	10.0%
171000	1	10.0%
202500	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
67500	1	10.0%
99000	1	10.0%
112500	1	10.0%
121500	1	10.0%
135000	2	20.0%
171000	1	10.0%
202500	1	10.0%
270000	1	10.0%
360000	1	10.0%

Value	Count	Frequency (%)
360000	1	10.0%
270000	1	10.0%
202500	1	10.0%
171000	1	10.0%
135000	2	20.0%
121500	1	10.0%
112500	1	10.0%
99000	1	10.0%
67500	1	10.0%

AMT_CREDIT
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	766661.4

Minimum	135000
Maximum	1560726
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	208.0 B

Quantile statistics

Minimum	135000
5-th percentile	214957.125
Q1	405399.375
median	501747.75
Q3	1225029.375
95-th percentile	1546899.3
Maximum	1560726
Range	1425726
Interquartile range (IQR)	819630

Descriptive statistics

Standard deviation	533429.0125
Coefficient of variation (CV)	0.6957817526
Kurtosis	-1.47175088
Mean	766661.4
Median Absolute Deviation (MAD)	277906.5
Skewness	0.5773194265
Sum	7666614
Variance	2.845465114 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1293502.5	1	10.0%
490495.5	1	10.0%
1560726	1	10.0%
406597.5	1	10.0%
1019610	1	10.0%
1530000	1	10.0%
513000	1	10.0%
312682.5	1	10.0%
405000	1	10.0%
135000	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
135000	1	10.0%
312682.5	1	10.0%
405000	1	10.0%
406597.5	1	10.0%
490495.5	1	10.0%
513000	1	10.0%
1019610	1	10.0%
1293502.5	1	10.0%
1530000	1	10.0%
1560726	1	10.0%

Value	Count	Frequency (%)
1560726	1	10.0%
1530000	1	10.0%
1293502.5	1	10.0%
1019610	1	10.0%
513000	1	10.0%
490495.5	1	10.0%
406597.5	1	10.0%
405000	1	10.0%
312682.5	1	10.0%
135000	1	10.0%

AMT_ANNUITY
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	28367.1

Minimum	6750
Maximum	42075
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	208.0 B

Quantile statistics

Minimum	6750
5-th percentile	12825
Q1	22574.25
median	28602
Q3	35230.5
95-th percentile	41726.7
Maximum	42075
Range	35325
Interquartile range (IQR)	12656.25

Descriptive statistics

Standard deviation	10698.44477
Coefficient of variation (CV)	0.3771427032
Kurtosis	0.5213427299
Mean	28367.1
Median Absolute Deviation (MAD)	6916.5
Skewness	-0.6422828635
Sum	283671
Variance	114456720.6
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
27517.5	1	10.0%
33826.5	1	10.0%
29686.5	1	10.0%
20250	1	10.0%
35698.5	1	10.0%
21865.5	1	10.0%
41301	1	10.0%
42075	1	10.0%
6750	1	10.0%
24700.5	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6750	1	10.0%
20250	1	10.0%
21865.5	1	10.0%
24700.5	1	10.0%
27517.5	1	10.0%
29686.5	1	10.0%
33826.5	1	10.0%
35698.5	1	10.0%
41301	1	10.0%
42075	1	10.0%

Value	Count	Frequency (%)
42075	1	10.0%
41301	1	10.0%
35698.5	1	10.0%
33826.5	1	10.0%
29686.5	1	10.0%
27517.5	1	10.0%
24700.5	1	10.0%
21865.5	1	10.0%
20250	1	10.0%
6750	1	10.0%

AMT_GOODS_PRICE
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	712350

Minimum	135000
Maximum	1530000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	208.0 B

Quantile statistics

Minimum	135000
5-th percentile	207900
Q1	364500
median	483750
Q3	1075500
95-th percentile	1469250
Maximum	1530000
Range	1395000
Interquartile range (IQR)	711000

Descriptive statistics

Standard deviation	492854.6692
Coefficient of variation (CV)	0.6918715087
Kurtosis	-1.125241744
Mean	712350
Median Absolute Deviation (MAD)	267750
Skewness	0.6730048923
Sum	7123500
Variance	2.42905725 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1129500	1	10.0%
135000	1	10.0%
1395000	1	10.0%
297000	1	10.0%
454500	1	10.0%
913500	1	10.0%
513000	1	10.0%
405000	1	10.0%
1530000	1	10.0%
351000	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
135000	1	10.0%
297000	1	10.0%
351000	1	10.0%
405000	1	10.0%
454500	1	10.0%
513000	1	10.0%
913500	1	10.0%
1129500	1	10.0%
1395000	1	10.0%
1530000	1	10.0%

Value	Count	Frequency (%)
1530000	1	10.0%
1395000	1	10.0%
1129500	1	10.0%
913500	1	10.0%
513000	1	10.0%
454500	1	10.0%
405000	1	10.0%
351000	1	10.0%
297000	1	10.0%
135000	1	10.0%

NAME_TYPE_SUITE
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	40.0%
Missing	0
Missing (%)	0.0%
Memory size	818.0 B

Unaccompanied	7
Spouse, partner	1
Family	1
Children	1

Length

Max length	15
Median length	13
Mean length	12
Min length	6

Characters and Unicode

Total characters	120
Distinct characters	22
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	30.0%

Sample

1st row	Unaccompanied
2nd row	Family
3rd row	Unaccompanied
4th row	Unaccompanied
5th row	Unaccompanied

Common Values

Value	Count	Frequency (%)
Unaccompanied	7	70.0%
Spouse, partner	1	10.0%
Family	1	10.0%
Children	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
unaccompanied	7	63.6%
family	1	9.1%
children	1	9.1%
partner	1	9.1%
spouse	1	9.1%

Most occurring characters

Value	Count	Frequency (%)
n	16	13.3%
a	16	13.3%
c	14	11.7%
e	10	8.3%
p	9	7.5%
i	9	7.5%
o	8	6.7%
m	8	6.7%
d	8	6.7%
U	7	5.8%
Other values (12)	15	12.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	108	90.0%
Uppercase Letter	10	8.3%
Other Punctuation	1	0.8%
Space Separator	1	0.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	16	14.8%
a	16	14.8%
c	14	13.0%
e	10	9.3%
p	9	8.3%
i	9	8.3%
o	8	7.4%
m	8	7.4%
d	8	7.4%
r	3	2.8%
Other values (6)	7	6.5%

Uppercase Letter

Value	Count	Frequency (%)
U	7	70.0%
F	1	10.0%
S	1	10.0%
C	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
,	1	100.0%

Space Separator

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	118	98.3%
Common	2	1.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	16	13.6%
a	16	13.6%
c	14	11.9%
e	10	8.5%
p	9	7.6%
i	9	7.6%
o	8	6.8%
m	8	6.8%
d	8	6.8%
U	7	5.9%
Other values (10)	13	11.0%

Common

Value	Count	Frequency (%)
,	1	50.0%
	1	50.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	120	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	16	13.3%
a	16	13.3%
c	14	11.7%
e	10	8.3%
p	9	7.5%
i	9	7.5%
o	8	6.7%
m	8	6.7%
d	8	6.7%
U	7	5.8%
Other values (12)	15	12.5%

NAME_INCOME_TYPE
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	40.0%
Missing	0
Missing (%)	0.0%
Memory size	801.0 B

Working	5
State servant	3
Pensioner	1
Commercial associate	1

Length

Max length	20
Median length	8
Mean length	10.3
Min length	7

Characters and Unicode

Total characters	103
Distinct characters	19
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	20.0%

Sample

1st row	Working
2nd row	State servant
3rd row	Working
4th row	Working
5th row	Working

Common Values

Value	Count	Frequency (%)
Working	5	50.0%
State servant	3	30.0%
Pensioner	1	10.0%
Commercial associate	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
working	5	35.7%
state	3	21.4%
servant	3	21.4%
pensioner	1	7.1%
associate	1	7.1%
commercial	1	7.1%

Most occurring characters

Value	Count	Frequency (%)
r	10	9.7%
n	10	9.7%
t	10	9.7%
e	10	9.7%
a	9	8.7%
o	8	7.8%
i	8	7.8%
s	6	5.8%
W	5	4.9%
k	5	4.9%
Other values (9)	22	21.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	89	86.4%
Uppercase Letter	10	9.7%
Space Separator	4	3.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	10	11.2%
n	10	11.2%
t	10	11.2%
e	10	11.2%
a	9	10.1%
o	8	9.0%
i	8	9.0%
s	6	6.7%
k	5	5.6%
g	5	5.6%
Other values (4)	8	9.0%

Uppercase Letter

Value	Count	Frequency (%)
W	5	50.0%
S	3	30.0%
C	1	10.0%
P	1	10.0%

Space Separator

Value	Count	Frequency (%)
	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	99	96.1%
Common	4	3.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	10	10.1%
n	10	10.1%
t	10	10.1%
e	10	10.1%
a	9	9.1%
o	8	8.1%
i	8	8.1%
s	6	6.1%
W	5	5.1%
k	5	5.1%
Other values (8)	18	18.2%

Common

Value	Count	Frequency (%)
	4	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	103	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	10	9.7%
n	10	9.7%
t	10	9.7%
e	10	9.7%
a	9	8.7%
o	8	7.8%
i	8	7.8%
s	6	5.8%
W	5	4.9%
k	5	4.9%
Other values (9)	22	21.4%

NAME_EDUCATION_TYPE
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	949.0 B

Secondary / secondary special	7
Higher education	3

Length

Max length	29
Median length	29
Mean length	25.1
Min length	16

Characters and Unicode

Total characters	251
Distinct characters	20
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Secondary / secondary special
2nd row	Higher education
3rd row	Secondary / secondary special
4th row	Secondary / secondary special
5th row	Secondary / secondary special

Common Values

Value	Count	Frequency (%)
Secondary / secondary special	7	70.0%
Higher education	3	30.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
secondary	14	41.2%
special	7	20.6%
	7	20.6%
higher	3	8.8%
education	3	8.8%

Most occurring characters

Value	Count	Frequency (%)
e	27	10.8%
c	24	9.6%
a	24	9.6%
	24	9.6%
o	17	6.8%
n	17	6.8%
d	17	6.8%
r	17	6.8%
y	14	5.6%
s	14	5.6%
Other values (10)	56	22.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	210	83.7%
Space Separator	24	9.6%
Uppercase Letter	10	4.0%
Other Punctuation	7	2.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	27	12.9%
c	24	11.4%
a	24	11.4%
o	17	8.1%
n	17	8.1%
d	17	8.1%
r	17	8.1%
y	14	6.7%
s	14	6.7%
i	13	6.2%
Other values (6)	26	12.4%

Uppercase Letter

Value	Count	Frequency (%)
S	7	70.0%
H	3	30.0%

Space Separator

Value	Count	Frequency (%)
	24	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	7	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	220	87.6%
Common	31	12.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	27	12.3%
c	24	10.9%
a	24	10.9%
o	17	7.7%
n	17	7.7%
d	17	7.7%
r	17	7.7%
y	14	6.4%
s	14	6.4%
i	13	5.9%
Other values (8)	36	16.4%

Common

Value	Count	Frequency (%)
	24	77.4%
/	7	22.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	251	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	27	10.8%
c	24	9.6%
a	24	9.6%
	24	9.6%
o	17	6.8%
n	17	6.8%
d	17	6.8%
r	17	6.8%
y	14	5.6%
s	14	5.6%
Other values (10)	56	22.3%

NAME_FAMILY_STATUS
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	30.0%
Missing	0
Missing (%)	0.0%
Memory size	827.0 B

Married	5
Single / not married	4
Civil marriage	1

Length

Max length	20
Median length	10.5
Mean length	12.9
Min length	7

Characters and Unicode

Total characters	129
Distinct characters	17
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	10.0%

Sample

1st row	Single / not married
2nd row	Married
3rd row	Single / not married
4th row	Civil marriage
5th row	Single / not married

Common Values

Value	Count	Frequency (%)
Married	5	50.0%
Single / not married	4	40.0%
Civil marriage	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
married	9	39.1%
not	4	17.4%
single	4	17.4%
	4	17.4%
civil	1	4.3%
marriage	1	4.3%

Most occurring characters

Value	Count	Frequency (%)
r	20	15.5%
i	16	12.4%
e	14	10.9%
	13	10.1%
a	11	8.5%
d	9	7.0%
n	8	6.2%
g	5	3.9%
l	5	3.9%
m	5	3.9%
Other values (7)	23	17.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	102	79.1%
Space Separator	13	10.1%
Uppercase Letter	10	7.8%
Other Punctuation	4	3.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	20	19.6%
i	16	15.7%
e	14	13.7%
a	11	10.8%
d	9	8.8%
n	8	7.8%
g	5	4.9%
l	5	4.9%
m	5	4.9%
o	4	3.9%
Other values (2)	5	4.9%

Uppercase Letter

Value	Count	Frequency (%)
M	5	50.0%
S	4	40.0%
C	1	10.0%

Space Separator

Value	Count	Frequency (%)
	13	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	112	86.8%
Common	17	13.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	20	17.9%
i	16	14.3%
e	14	12.5%
a	11	9.8%
d	9	8.0%
n	8	7.1%
g	5	4.5%
l	5	4.5%
m	5	4.5%
M	5	4.5%
Other values (5)	14	12.5%

Common

Value	Count	Frequency (%)
	13	76.5%
/	4	23.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	129	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	20	15.5%
i	16	12.4%
e	14	10.9%
	13	10.1%
a	11	8.5%
d	9	7.0%
n	8	6.2%
g	5	3.9%
l	5	3.9%
m	5	3.9%
Other values (7)	23	17.8%

NAME_HOUSING_TYPE
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	868.0 B

House / apartment	10

Length

Max length	17
Median length	17
Mean length	17
Min length	17

Characters and Unicode

Total characters	170
Distinct characters	13
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	House / apartment
2nd row	House / apartment
3rd row	House / apartment
4th row	House / apartment
5th row	House / apartment

Common Values

Value	Count	Frequency (%)
House / apartment	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
apartment	10	33.3%
house	10	33.3%
	10	33.3%

Most occurring characters

Value	Count	Frequency (%)
e	20	11.8%
	20	11.8%
a	20	11.8%
t	20	11.8%
H	10	5.9%
o	10	5.9%
u	10	5.9%
s	10	5.9%
/	10	5.9%
p	10	5.9%
Other values (3)	30	17.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	130	76.5%
Space Separator	20	11.8%
Uppercase Letter	10	5.9%
Other Punctuation	10	5.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	20	15.4%
a	20	15.4%
t	20	15.4%
o	10	7.7%
u	10	7.7%
s	10	7.7%
p	10	7.7%
r	10	7.7%
m	10	7.7%
n	10	7.7%

Uppercase Letter

Value	Count	Frequency (%)
H	10	100.0%

Space Separator

Value	Count	Frequency (%)
	20	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	140	82.4%
Common	30	17.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	20	14.3%
a	20	14.3%
t	20	14.3%
H	10	7.1%
o	10	7.1%
u	10	7.1%
s	10	7.1%
p	10	7.1%
r	10	7.1%
m	10	7.1%

Common

Value	Count	Frequency (%)
	20	66.7%
/	10	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	170	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	20	11.8%
	20	11.8%
a	20	11.8%
t	20	11.8%
H	10	5.9%
o	10	5.9%
u	10	5.9%
s	10	5.9%
/	10	5.9%
p	10	5.9%
Other values (3)	30	17.6%

REGION_POPULATION_RELATIVE
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	90.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.0182085

Minimum	0.003122
Maximum	0.035792
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	208.0 B

Quantile statistics

Minimum	0.003122
5-th percentile	0.00331055
Q1	0.00852225
median	0.0187175
Q3	0.0264195
95-th percentile	0.035792
Maximum	0.035792
Range	0.03267
Interquartile range (IQR)	0.01789725

Descriptive statistics

Standard deviation	0.01221928622
Coefficient of variation (CV)	0.6710759384
Kurtosis	-1.241070031
Mean	0.0182085
Median Absolute Deviation (MAD)	0.010322
Skewness	0.2912015997
Sum	0.182085
Variance	0.0001493109558
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0.035792	2	20.0%
0.010032	1	10.0%
0.003541	1	10.0%
0.028663	1	10.0%
0.003122	1	10.0%
0.018801	1	10.0%
0.018634	1	10.0%
0.019689	1	10.0%
0.008019	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.003122	1	10.0%
0.003541	1	10.0%
0.008019	1	10.0%
0.010032	1	10.0%
0.018634	1	10.0%
0.018801	1	10.0%
0.019689	1	10.0%
0.028663	1	10.0%
0.035792	2	20.0%

Value	Count	Frequency (%)
0.035792	2	20.0%
0.028663	1	10.0%
0.019689	1	10.0%
0.018801	1	10.0%
0.018634	1	10.0%
0.010032	1	10.0%
0.008019	1	10.0%
0.003541	1	10.0%
0.003122	1	10.0%

DAYS_BIRTH
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-16834.6

Minimum	-20099
Maximum	-9461
Zeros	0
Zeros (%)	0.0%
Negative	10
Negative (%)	100.0%
Memory size	208.0 B

Quantile statistics

Minimum	-20099
5-th percentile	-20023.85
Q1	-19035.75
median	-17895.5
Q3	-15043
95-th percentile	-11403.65
Maximum	-9461
Range	10638
Interquartile range (IQR)	3992.75

Descriptive statistics

Standard deviation	3386.869521
Coefficient of variation (CV)	-0.2011850309
Kurtosis	1.205590712
Mean	-16834.6
Median Absolute Deviation (MAD)	1593.5
Skewness	1.247555439
Sum	-168346
Variance	11470885.16
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
-18850	1	10.0%
-16765	1	10.0%
-19932	1	10.0%
-13778	1	10.0%
-14469	1	10.0%
-19046	1	10.0%
-9461	1	10.0%
-19005	1	10.0%
-20099	1	10.0%
-16941	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-20099	1	10.0%
-19932	1	10.0%
-19046	1	10.0%
-19005	1	10.0%
-18850	1	10.0%
-16941	1	10.0%
-16765	1	10.0%
-14469	1	10.0%
-13778	1	10.0%
-9461	1	10.0%

Value	Count	Frequency (%)
-9461	1	10.0%
-13778	1	10.0%
-14469	1	10.0%
-16765	1	10.0%
-16941	1	10.0%
-18850	1	10.0%
-19005	1	10.0%
-19046	1	10.0%
-19932	1	10.0%
-20099	1	10.0%

DAYS_EMPLOYED
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	34993

Minimum	-3130
Maximum	365243
Zeros	0
Zeros (%)	0.0%
Negative	9
Negative (%)	90.0%
Memory size	208.0 B

Quantile statistics

Minimum	-3130
5-th percentile	-3089.05
Q1	-2783.25
median	-1388
Q3	-496
95-th percentile	200782.4
Maximum	365243
Range	368373
Interquartile range (IQR)	2287.25

Descriptive statistics

Standard deviation	116043.2285
Coefficient of variation (CV)	3.31618405
Kurtosis	9.997532692
Mean	34993
Median Absolute Deviation (MAD)	1051
Skewness	3.161745518
Sum	349930
Variance	1.346603087 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
-2019	1	10.0%
-3039	1	10.0%
-3038	1	10.0%
-637	1	10.0%
-449	1	10.0%
365243	1	10.0%
-3130	1	10.0%
-1188	1	10.0%
-1588	1	10.0%
-225	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-3130	1	10.0%
-3039	1	10.0%
-3038	1	10.0%
-2019	1	10.0%
-1588	1	10.0%
-1188	1	10.0%
-637	1	10.0%
-449	1	10.0%
-225	1	10.0%
365243	1	10.0%

Value	Count	Frequency (%)
365243	1	10.0%
-225	1	10.0%
-449	1	10.0%
-637	1	10.0%
-1188	1	10.0%
-1588	1	10.0%
-2019	1	10.0%
-3038	1	10.0%
-3039	1	10.0%
-3130	1	10.0%

DAYS_REGISTRATION
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-5588.2

Minimum	-14437
Maximum	-1186
Zeros	0
Zeros (%)	0.0%
Negative	10
Negative (%)	100.0%
Memory size	208.0 B

Quantile statistics

Minimum	-14437
5-th percentile	-12365.2
Q1	-6812.75
median	-4454
Q3	-3801
95-th percentile	-1198.15
Maximum	-1186
Range	13251
Interquartile range (IQR)	3011.75

Descriptive statistics

Standard deviation	4037.971075
Coefficient of variation (CV)	-0.7225888613
Kurtosis	1.596266945
Mean	-5588.2
Median Absolute Deviation (MAD)	1889.5
Skewness	-1.252131009
Sum	-55882
Variance	16305210.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
-14437	1	10.0%
-9833	1	10.0%
-7427	1	10.0%
-4597	1	10.0%
-1213	1	10.0%
-4970	1	10.0%
-4311	1	10.0%
-4260	1	10.0%
-1186	1	10.0%
-3648	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-14437	1	10.0%
-9833	1	10.0%
-7427	1	10.0%
-4970	1	10.0%
-4597	1	10.0%
-4311	1	10.0%
-4260	1	10.0%
-3648	1	10.0%
-1213	1	10.0%
-1186	1	10.0%

Value	Count	Frequency (%)
-1186	1	10.0%
-1213	1	10.0%
-3648	1	10.0%
-4260	1	10.0%
-4311	1	10.0%
-4597	1	10.0%
-4970	1	10.0%
-7427	1	10.0%
-9833	1	10.0%
-14437	1	10.0%

DAYS_ID_PUBLISH
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-2181.8

Minimum	-3992
Maximum	-291
Zeros	0
Zeros (%)	0.0%
Negative	10
Negative (%)	100.0%
Memory size	208.0 B

Quantile statistics

Minimum	-3992
5-th percentile	-3776.9
Q1	-3226.25
median	-2408
Q3	-994.25
95-th percentile	-374.7
Maximum	-291
Range	3701
Interquartile range (IQR)	2232

Descriptive statistics

Standard deviation	1326.392501
Coefficient of variation (CV)	-0.6079349624
Kurtosis	-1.254027435
Mean	-2181.8
Median Absolute Deviation (MAD)	1078
Skewness	0.3029648975
Sum	-21818
Variance	1759317.067
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
-2531	1	10.0%
-3992	1	10.0%
-477	1	10.0%
-619	1	10.0%
-3514	1	10.0%
-2120	1	10.0%
-2437	1	10.0%
-2379	1	10.0%
-291	1	10.0%
-3458	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-3992	1	10.0%
-3514	1	10.0%
-3458	1	10.0%
-2531	1	10.0%
-2437	1	10.0%
-2379	1	10.0%
-2120	1	10.0%
-619	1	10.0%
-477	1	10.0%
-291	1	10.0%

Value	Count	Frequency (%)
-291	1	10.0%
-477	1	10.0%
-619	1	10.0%
-2120	1	10.0%
-2379	1	10.0%
-2437	1	10.0%
-2531	1	10.0%
-3458	1	10.0%
-3514	1	10.0%
-3992	1	10.0%

OWN_CAR_AGE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	3
Distinct (%)	100.0%
Missing	7
Missing (%)	70.0%
Memory size	590.0 B

26.0	1
8.0	1
17.0	1

Length

Max length	4
Median length	4
Mean length	3.666666667
Min length	3

Characters and Unicode

Total characters	11
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	100.0%

Sample

1st row	26.0
2nd row	17.0
3rd row	8.0

Common Values

Value	Count	Frequency (%)
26.0	1	10.0%
8.0	1	10.0%
17.0	1	10.0%
(Missing)	7	70.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
17.0	1	33.3%
8.0	1	33.3%
26.0	1	33.3%

Most occurring characters

Value	Count	Frequency (%)
.	3	27.3%
0	3	27.3%
2	1	9.1%
6	1	9.1%
1	1	9.1%
7	1	9.1%
8	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	8	72.7%
Other Punctuation	3	27.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3	37.5%
2	1	12.5%
6	1	12.5%
1	1	12.5%
7	1	12.5%
8	1	12.5%

Other Punctuation

Value	Count	Frequency (%)
.	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	3	27.3%
0	3	27.3%
2	1	9.1%
6	1	9.1%
1	1	9.1%
7	1	9.1%
8	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	3	27.3%
0	3	27.3%
2	1	9.1%
6	1	9.1%
1	1	9.1%
7	1	9.1%
8	1	9.1%

FLAG_MOBIL
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

1	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	10	100.0%

FLAG_EMP_PHONE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

1	9
0	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	10.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	9	90.0%
0	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	9	90.0%
0	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
1	9	90.0%
0	1	10.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	9	90.0%
0	1	10.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	9	90.0%
0	1	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	9	90.0%
0	1	10.0%

FLAG_WORK_PHONE
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	7
1	3

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	7	70.0%
1	3	30.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	7	70.0%
1	3	30.0%

Most occurring characters

Value	Count	Frequency (%)
0	7	70.0%
1	3	30.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	7	70.0%
1	3	30.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	7	70.0%
1	3	30.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	7	70.0%
1	3	30.0%

FLAG_CONT_MOBILE
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

1	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	10	100.0%

FLAG_PHONE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

1	5
0	5

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
1	5	50.0%
0	5	50.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	5	50.0%
1	5	50.0%

Most occurring characters

Value	Count	Frequency (%)
1	5	50.0%
0	5	50.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	5	50.0%
0	5	50.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	5	50.0%
0	5	50.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	5	50.0%
0	5	50.0%

FLAG_EMAIL
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

OCCUPATION_TYPE
Categorical

HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	44.4%
Missing	1
Missing (%)	10.0%
Memory size	752.0 B

Laborers	5
Core staff	2
Accountants	1
Managers	1

Length

Max length	11
Median length	8
Mean length	8.777777778
Min length	8

Characters and Unicode

Total characters	79
Distinct characters	17
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	22.2%

Sample

1st row	Laborers
2nd row	Core staff
3rd row	Laborers
4th row	Laborers
5th row	Core staff

Common Values

Value	Count	Frequency (%)
Laborers	5	50.0%
Core staff	2	20.0%
Accountants	1	10.0%
Managers	1	10.0%
(Missing)	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
laborers	5	45.5%
core	2	18.2%
staff	2	18.2%
accountants	1	9.1%
managers	1	9.1%

Most occurring characters

Value	Count	Frequency (%)
r	13	16.5%
a	10	12.7%
s	9	11.4%
o	8	10.1%
e	8	10.1%
L	5	6.3%
b	5	6.3%
t	4	5.1%
f	4	5.1%
n	3	3.8%
Other values (7)	10	12.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	68	86.1%
Uppercase Letter	9	11.4%
Space Separator	2	2.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	13	19.1%
a	10	14.7%
s	9	13.2%
o	8	11.8%
e	8	11.8%
b	5	7.4%
t	4	5.9%
f	4	5.9%
n	3	4.4%
c	2	2.9%
Other values (2)	2	2.9%

Uppercase Letter

Value	Count	Frequency (%)
L	5	55.6%
C	2	22.2%
A	1	11.1%
M	1	11.1%

Space Separator

Value	Count	Frequency (%)
	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	77	97.5%
Common	2	2.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	13	16.9%
a	10	13.0%
s	9	11.7%
o	8	10.4%
e	8	10.4%
L	5	6.5%
b	5	6.5%
t	4	5.2%
f	4	5.2%
n	3	3.9%
Other values (6)	8	10.4%

Common

Value	Count	Frequency (%)
	2	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	79	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	13	16.5%
a	10	12.7%
s	9	11.4%
o	8	10.1%
e	8	10.1%
L	5	6.3%
b	5	6.3%
t	4	5.1%
f	4	5.1%
n	3	3.8%
Other values (7)	10	12.7%

CNT_FAM_MEMBERS
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	30.0%
Missing	0
Missing (%)	0.0%
Memory size	728.0 B

2.0	5
1.0	4
3.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	30
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	10.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	2.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
2.0	5	50.0%
1.0	4	40.0%
3.0	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	5	50.0%
1.0	4	40.0%
3.0	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
.	10	33.3%
0	10	33.3%
2	5	16.7%
1	4	13.3%
3	1	3.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	20	66.7%
Other Punctuation	10	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	50.0%
2	5	25.0%
1	4	20.0%
3	1	5.0%

Other Punctuation

Value	Count	Frequency (%)
.	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	10	33.3%
0	10	33.3%
2	5	16.7%
1	4	13.3%
3	1	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	10	33.3%
0	10	33.3%
2	5	16.7%
1	4	13.3%
3	1	3.3%

REGION_RATING_CLIENT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	30.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

2	8
1	1
3	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	20.0%

Sample

1st row	2
2nd row	1
3rd row	2
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	8	80.0%
3	1	10.0%
1	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

REGION_RATING_CLIENT_W_CITY
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	30.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

2	8
1	1
3	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	20.0%

Sample

1st row	2
2nd row	1
3rd row	2
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	8	80.0%
3	1	10.0%
1	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	8	80.0%
1	1	10.0%
3	1	10.0%

WEEKDAY_APPR_PROCESS_START
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	40.0%
Missing	0
Missing (%)	0.0%
Memory size	774.0 B

WEDNESDAY	4
MONDAY	3
THURSDAY	2
SUNDAY	1

Length

Max length	9
Median length	8
Mean length	7.6
Min length	6

Characters and Unicode

Total characters	76
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	10.0%

Sample

1st row	WEDNESDAY
2nd row	MONDAY
3rd row	MONDAY
4th row	WEDNESDAY
5th row	THURSDAY

Common Values

Value	Count	Frequency (%)
WEDNESDAY	4	40.0%
MONDAY	3	30.0%
THURSDAY	2	20.0%
SUNDAY	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
wednesday	4	40.0%
monday	3	30.0%
thursday	2	20.0%
sunday	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
D	14	18.4%
A	10	13.2%
Y	10	13.2%
E	8	10.5%
N	8	10.5%
S	7	9.2%
W	4	5.3%
M	3	3.9%
O	3	3.9%
U	3	3.9%
Other values (3)	6	7.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	76	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
D	14	18.4%
A	10	13.2%
Y	10	13.2%
E	8	10.5%
N	8	10.5%
S	7	9.2%
W	4	5.3%
M	3	3.9%
O	3	3.9%
U	3	3.9%
Other values (3)	6	7.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	76	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
D	14	18.4%
A	10	13.2%
Y	10	13.2%
E	8	10.5%
N	8	10.5%
S	7	9.2%
W	4	5.3%
M	3	3.9%
O	3	3.9%
U	3	3.9%
Other values (3)	6	7.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	76	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
D	14	18.4%
A	10	13.2%
Y	10	13.2%
E	8	10.5%
N	8	10.5%
S	7	9.2%
W	4	5.3%
M	3	3.9%
O	3	3.9%
U	3	3.9%
Other values (3)	6	7.9%

HOUR_APPR_PROCESS_START
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	70.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12.8

Minimum	8
Maximum	17
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	208.0 B

Quantile statistics

Minimum	8
5-th percentile	8.45
Q1	10.25
median	12.5
Q3	16
95-th percentile	16.55
Maximum	17
Range	9
Interquartile range (IQR)	5.75

Descriptive statistics

Standard deviation	3.359894178
Coefficient of variation (CV)	0.2624917327
Kurtosis	-1.85662416
Mean	12.8
Median Absolute Deviation (MAD)	3.5
Skewness	-0.09139770418
Sum	128
Variance	11.28888889
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
16	3	30.0%
11	2	20.0%
14	1	10.0%
10	1	10.0%
9	1	10.0%
8	1	10.0%
17	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
8	1	10.0%
9	1	10.0%
10	1	10.0%
11	2	20.0%
14	1	10.0%
16	3	30.0%
17	1	10.0%

Value	Count	Frequency (%)
17	1	10.0%
16	3	30.0%
14	1	10.0%
11	2	20.0%
10	1	10.0%
9	1	10.0%
8	1	10.0%

REG_REGION_NOT_LIVE_REGION
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

REG_REGION_NOT_WORK_REGION
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

LIVE_REGION_NOT_WORK_REGION
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

REG_CITY_NOT_LIVE_CITY
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

REG_CITY_NOT_WORK_CITY
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	8
1	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring characters

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

LIVE_CITY_NOT_WORK_CITY
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	8
1	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring characters

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

ORGANIZATION_TYPE
Categorical

HIGH CORRELATION

Distinct	7
Distinct (%)	70.0%
Missing	0
Missing (%)	0.0%
Memory size	812.0 B

Business Entity Type 3	3
Other	2
School	1
XNA	1
Religion	1
Other values (2)	2

Length

Max length	22
Median length	9
Mean length	11.4
Min length	3

Characters and Unicode

Total characters	114
Distinct characters	28
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	50.0%

Sample

1st row	Business Entity Type 3
2nd row	School
3rd row	Government
4th row	Business Entity Type 3
5th row	Religion

Common Values

Value	Count	Frequency (%)
Business Entity Type 3	3	30.0%
Other	2	20.0%
School	1	10.0%
XNA	1	10.0%
Religion	1	10.0%
Electricity	1	10.0%
Government	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
entity	3	15.8%
type	3	15.8%
3	3	15.8%
business	3	15.8%
other	2	10.5%
electricity	1	5.3%
school	1	5.3%
government	1	5.3%
religion	1	5.3%
xna	1	5.3%

Most occurring characters

Value	Count	Frequency (%)
e	12	10.5%
t	11	9.6%
i	10	8.8%
s	9	7.9%
n	9	7.9%
	9	7.9%
y	7	6.1%
E	4	3.5%
o	4	3.5%
r	4	3.5%
Other values (18)	35	30.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	84	73.7%
Uppercase Letter	18	15.8%
Space Separator	9	7.9%
Decimal Number	3	2.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	12	14.3%
t	11	13.1%
i	10	11.9%
s	9	10.7%
n	9	10.7%
y	7	8.3%
o	4	4.8%
r	4	4.8%
u	3	3.6%
p	3	3.6%
Other values (6)	12	14.3%

Uppercase Letter

Value	Count	Frequency (%)
E	4	22.2%
B	3	16.7%
T	3	16.7%
O	2	11.1%
S	1	5.6%
G	1	5.6%
R	1	5.6%
X	1	5.6%
N	1	5.6%
A	1	5.6%

Space Separator

Value	Count	Frequency (%)
	9	100.0%

Decimal Number

Value	Count	Frequency (%)
3	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	102	89.5%
Common	12	10.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	12	11.8%
t	11	10.8%
i	10	9.8%
s	9	8.8%
n	9	8.8%
y	7	6.9%
E	4	3.9%
o	4	3.9%
r	4	3.9%
B	3	2.9%
Other values (16)	29	28.4%

Common

Value	Count	Frequency (%)
	9	75.0%
3	3	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	114	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	12	10.5%
t	11	9.6%
i	10	8.8%
s	9	7.9%
n	9	7.9%
	9	7.9%
y	7	6.1%
E	4	3.5%
o	4	3.5%
r	4	3.5%
Other values (18)	35	30.7%

EXT_SOURCE_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	4
Distinct (%)	100.0%
Missing	6
Missing (%)	60.0%
Memory size	669.0 B

0.08303696739132256	1
0.5873340468730377	1
0.7747614130547695	1
0.3112673113812225	1

Length

Max length	19
Median length	18
Mean length	18.25
Min length	18

Characters and Unicode

Total characters	73
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	100.0%

Sample

1st row	0.08303696739132256
2nd row	0.3112673113812225
3rd row	0.7747614130547695
4th row	0.5873340468730377

Common Values

Value	Count	Frequency (%)
0.08303696739132256	1	10.0%
0.5873340468730377	1	10.0%
0.7747614130547695	1	10.0%
0.3112673113812225	1	10.0%
(Missing)	6	60.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.3112673113812225	1	25.0%
0.7747614130547695	1	25.0%
0.5873340468730377	1	25.0%
0.08303696739132256	1	25.0%

Most occurring characters

Value	Count	Frequency (%)
3	12	16.4%
7	10	13.7%
0	9	12.3%
1	8	11.0%
6	7	9.6%
2	6	8.2%
5	5	6.8%
4	5	6.8%
.	4	5.5%
8	4	5.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	69	94.5%
Other Punctuation	4	5.5%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	12	17.4%
7	10	14.5%
0	9	13.0%
1	8	11.6%
6	7	10.1%
2	6	8.7%
5	5	7.2%
4	5	7.2%
8	4	5.8%
9	3	4.3%

Other Punctuation

Value	Count	Frequency (%)
.	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	73	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	12	16.4%
7	10	13.7%
0	9	12.3%
1	8	11.0%
6	7	9.6%
2	6	8.2%
5	5	6.8%
4	5	6.8%
.	4	5.5%
8	4	5.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	12	16.4%
7	10	13.7%
0	9	12.3%
1	8	11.0%
6	7	9.6%
2	6	8.2%
5	5	6.8%
4	5	6.8%
.	4	5.5%
8	4	5.5%

EXT_SOURCE_2
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.5159181216

Minimum	0.205747288
Maximum	0.7466436295
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	208.0 B

Quantile statistics

Minimum	0.205747288
5-th percentile	0.2314878751
Q1	0.3306098982
median	0.5890789293
Q3	0.6983198874
95-th percentile	0.7364539295
Maximum	0.7466436295
Range	0.5408963415
Interquartile range (IQR)	0.3677099892

Descriptive statistics

Standard deviation	0.2083116855
Coefficient of variation (CV)	0.4037688865
Kurtosis	-1.772926701
Mean	0.5159181216
Median Absolute Deviation (MAD)	0.1462428113
Skewness	-0.379016375
Sum	5.159181216
Variance	0.04339375832
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0.205747288	1	10.0%
0.7239998517	1	10.0%
0.322738287	1	10.0%
0.7142792864	1	10.0%
0.354224732	1	10.0%
0.6504416904	1	10.0%
0.2629485927	1	10.0%
0.7466436295	1	10.0%
0.5559120834	1	10.0%
0.6222457753	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.205747288	1	10.0%
0.2629485927	1	10.0%
0.322738287	1	10.0%
0.354224732	1	10.0%
0.5559120834	1	10.0%
0.6222457753	1	10.0%
0.6504416904	1	10.0%
0.7142792864	1	10.0%
0.7239998517	1	10.0%
0.7466436295	1	10.0%

Value	Count	Frequency (%)
0.7466436295	1	10.0%
0.7239998517	1	10.0%
0.7142792864	1	10.0%
0.6504416904	1	10.0%
0.6222457753	1	10.0%
0.5559120834	1	10.0%
0.354224732	1	10.0%
0.322738287	1	10.0%
0.2629485927	1	10.0%
0.205747288	1	10.0%

EXT_SOURCE_3
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	100.0%
Missing	4
Missing (%)	40.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.5457678447

Minimum	0.1393757801
Maximum	0.7517237148
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	208.0 B

Quantile statistics

Minimum	0.1393757801
5-th percentile	0.2275468585
Q1	0.504208683
median	0.5809403943
Q3	0.7024816025
95-th percentile	0.7461844588
Maximum	0.7517237148
Range	0.6123479347
Interquartile range (IQR)	0.1982729195

Descriptive statistics

Standard deviation	0.2235884612
Coefficient of variation (CV)	0.4096768679
Kurtosis	2.224809771
Mean	0.5457678447
Median Absolute Deviation (MAD)	0.1187532984
Skewness	-1.392900926
Sum	3.274607068
Variance	0.04999179998
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0.7295666907	1	10.0%
0.1393757801	1	10.0%
0.5406544504	1	10.0%
0.7517237148	1	10.0%
0.6212263381	1	10.0%
0.4920600939	1	10.0%
(Missing)	4	40.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.1393757801	1	10.0%
0.4920600939	1	10.0%
0.5406544504	1	10.0%
0.6212263381	1	10.0%
0.7295666907	1	10.0%
0.7517237148	1	10.0%

Value	Count	Frequency (%)
0.7517237148	1	10.0%
0.7295666907	1	10.0%
0.6212263381	1	10.0%
0.5406544504	1	10.0%
0.4920600939	1	10.0%
0.1393757801	1	10.0%

APARTMENTS_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0247	1
0.0959	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0247
2nd row	0.0959

Common Values

Value	Count	Frequency (%)
0.0247	1	10.0%
0.0959	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0959	1	50.0%
0.0247	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
9	2	16.7%
2	1	8.3%
4	1	8.3%
7	1	8.3%
5	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
9	2	20.0%
2	1	10.0%
4	1	10.0%
7	1	10.0%
5	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
9	2	16.7%
2	1	8.3%
4	1	8.3%
7	1	8.3%
5	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
9	2	16.7%
2	1	8.3%
4	1	8.3%
7	1	8.3%
5	1	8.3%

BASEMENTAREA_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0369	1
0.0529	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0369
2nd row	0.0529

Common Values

Value	Count	Frequency (%)
0.0369	1	10.0%
0.0529	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0529	1	50.0%
0.0369	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
9	2	16.7%
3	1	8.3%
6	1	8.3%
5	1	8.3%
2	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
9	2	20.0%
3	1	10.0%
6	1	10.0%
5	1	10.0%
2	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
9	2	16.7%
3	1	8.3%
6	1	8.3%
5	1	8.3%
2	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
9	2	16.7%
3	1	8.3%
6	1	8.3%
5	1	8.3%
2	1	8.3%

YEARS_BEGINEXPLUATATION_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.9851	1
0.9722	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.9722
2nd row	0.9851

Common Values

Value	Count	Frequency (%)
0.9851	1	10.0%
0.9722	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.9722	1	50.0%
0.9851	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
9	2	16.7%
2	2	16.7%
7	1	8.3%
8	1	8.3%
5	1	8.3%
1	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	2	20.0%
9	2	20.0%
2	2	20.0%
7	1	10.0%
8	1	10.0%
5	1	10.0%
1	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
9	2	16.7%
2	2	16.7%
7	1	8.3%
8	1	8.3%
5	1	8.3%
1	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
9	2	16.7%
2	2	16.7%
7	1	8.3%
8	1	8.3%
5	1	8.3%
1	1	8.3%

YEARS_BUILD_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	586.0 B

0.7959999999999999	1
0.6192	1

Length

Max length	18
Median length	12
Mean length	12
Min length	6

Characters and Unicode

Total characters	24
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.6192
2nd row	0.7959999999999999

Common Values

Value	Count	Frequency (%)
0.7959999999999999	1	10.0%
0.6192	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.6192	1	50.0%
0.7959999999999999	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
9	15	62.5%
0	2	8.3%
.	2	8.3%
6	1	4.2%
1	1	4.2%
2	1	4.2%
7	1	4.2%
5	1	4.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	22	91.7%
Other Punctuation	2	8.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
9	15	68.2%
0	2	9.1%
6	1	4.5%
1	1	4.5%
2	1	4.5%
7	1	4.5%
5	1	4.5%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	24	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
9	15	62.5%
0	2	8.3%
.	2	8.3%
6	1	4.2%
1	1	4.2%
2	1	4.2%
7	1	4.2%
5	1	4.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
9	15	62.5%
0	2	8.3%
.	2	8.3%
6	1	4.2%
1	1	4.2%
2	1	4.2%
7	1	4.2%
5	1	4.2%

COMMONAREA_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0143	1
0.0605	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0143
2nd row	0.0605

Common Values

Value	Count	Frequency (%)
0.0143	1	10.0%
0.0605	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0605	1	50.0%
0.0143	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
1	1	8.3%
4	1	8.3%
3	1	8.3%
6	1	8.3%
5	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	50.0%
1	1	10.0%
4	1	10.0%
3	1	10.0%
6	1	10.0%
5	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
1	1	8.3%
4	1	8.3%
3	1	8.3%
6	1	8.3%
5	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
1	1	8.3%
4	1	8.3%
3	1	8.3%
6	1	8.3%
5	1	8.3%

ELEVATORS_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	569.0 B

0.08	1
0.0	1

Length

Max length	4
Median length	3.5
Mean length	3.5
Min length	3

Characters and Unicode

Total characters	7
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0
2nd row	0.08

Common Values

Value	Count	Frequency (%)
0.08	1	10.0%
0.0	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	1	50.0%
0.08	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	57.1%
.	2	28.6%
8	1	14.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5	71.4%
Other Punctuation	2	28.6%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	80.0%
8	1	20.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	7	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	57.1%
.	2	28.6%
8	1	14.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	57.1%
.	2	28.6%
8	1	14.3%

ENTRANCES_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	573.0 B

0.069	1
0.0345	1

Length

Max length	6
Median length	5.5
Mean length	5.5
Min length	5

Characters and Unicode

Total characters	11
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.069
2nd row	0.0345

Common Values

Value	Count	Frequency (%)
0.069	1	10.0%
0.0345	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0345	1	50.0%
0.069	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
6	1	9.1%
9	1	9.1%
3	1	9.1%
4	1	9.1%
5	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9	81.8%
Other Punctuation	2	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	44.4%
6	1	11.1%
9	1	11.1%
3	1	11.1%
4	1	11.1%
5	1	11.1%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
6	1	9.1%
9	1	9.1%
3	1	9.1%
4	1	9.1%
5	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
6	1	9.1%
9	1	9.1%
3	1	9.1%
4	1	9.1%
5	1	9.1%

FLOORSMAX_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0833	1
0.2917	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0833
2nd row	0.2917

Common Values

Value	Count	Frequency (%)
0.0833	1	10.0%
0.2917	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.2917	1	50.0%
0.0833	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	3	25.0%
.	2	16.7%
3	2	16.7%
8	1	8.3%
2	1	8.3%
9	1	8.3%
1	1	8.3%
7	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3	30.0%
3	2	20.0%
8	1	10.0%
2	1	10.0%
9	1	10.0%
1	1	10.0%
7	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3	25.0%
.	2	16.7%
3	2	16.7%
8	1	8.3%
2	1	8.3%
9	1	8.3%
1	1	8.3%
7	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3	25.0%
.	2	16.7%
3	2	16.7%
8	1	8.3%
2	1	8.3%
9	1	8.3%
1	1	8.3%
7	1	8.3%

FLOORSMIN_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	573.0 B

0.3333	1
0.125	1

Length

Max length	6
Median length	5.5
Mean length	5.5
Min length	5

Characters and Unicode

Total characters	11
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.125
2nd row	0.3333

Common Values

Value	Count	Frequency (%)
0.3333	1	10.0%
0.125	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.125	1	50.0%
0.3333	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
3	4	36.4%
0	2	18.2%
.	2	18.2%
1	1	9.1%
2	1	9.1%
5	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9	81.8%
Other Punctuation	2	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	4	44.4%
0	2	22.2%
1	1	11.1%
2	1	11.1%
5	1	11.1%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	4	36.4%
0	2	18.2%
.	2	18.2%
1	1	9.1%
2	1	9.1%
5	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	4	36.4%
0	2	18.2%
.	2	18.2%
1	1	9.1%
2	1	9.1%
5	1	9.1%

LANDAREA_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	588.0 B

0.0369	1
0.013000000000000001	1

Length

Max length	20
Median length	13
Mean length	13
Min length	6

Characters and Unicode

Total characters	26
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0369
2nd row	0.013000000000000001

Common Values

Value	Count	Frequency (%)
0.0369	1	10.0%
0.013000000000000001	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.013000000000000001	1	50.0%
0.0369	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	18	69.2%
.	2	7.7%
3	2	7.7%
1	2	7.7%
6	1	3.8%
9	1	3.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	24	92.3%
Other Punctuation	2	7.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	18	75.0%
3	2	8.3%
1	2	8.3%
6	1	4.2%
9	1	4.2%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	26	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	18	69.2%
.	2	7.7%
3	2	7.7%
1	2	7.7%
6	1	3.8%
9	1	3.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	26	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	18	69.2%
.	2	7.7%
3	2	7.7%
1	2	7.7%
6	1	3.8%
9	1	3.8%

LIVINGAPARTMENTS_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0202	1
0.0773	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0202
2nd row	0.0773

Common Values

Value	Count	Frequency (%)
0.0202	1	10.0%
0.0773	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0773	1	50.0%
0.0202	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
2	2	16.7%
7	2	16.7%
3	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	50.0%
2	2	20.0%
7	2	20.0%
3	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
2	2	16.7%
7	2	16.7%
3	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
2	2	16.7%
7	2	16.7%
3	1	8.3%

LIVINGAREA_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	573.0 B

0.0549	1
0.019	1

Length

Max length	6
Median length	5.5
Mean length	5.5
Min length	5

Characters and Unicode

Total characters	11
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.019
2nd row	0.0549

Common Values

Value	Count	Frequency (%)
0.0549	1	10.0%
0.019	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.019	1	50.0%
0.0549	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
9	2	18.2%
1	1	9.1%
5	1	9.1%
4	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9	81.8%
Other Punctuation	2	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	44.4%
9	2	22.2%
1	1	11.1%
5	1	11.1%
4	1	11.1%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
9	2	18.2%
1	1	9.1%
5	1	9.1%
4	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
9	2	18.2%
1	1	9.1%
5	1	9.1%
4	1	9.1%

NONLIVINGAPARTMENTS_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	571.0 B

0.0039	1
0.0	1

Length

Max length	6
Median length	4.5
Mean length	4.5
Min length	3

Characters and Unicode

Total characters	9
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0
2nd row	0.0039

Common Values

Value	Count	Frequency (%)
0.0039	1	10.0%
0.0	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	1	50.0%
0.0039	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
3	1	11.1%
9	1	11.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	7	77.8%
Other Punctuation	2	22.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	71.4%
3	1	14.3%
9	1	14.3%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	9	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
3	1	11.1%
9	1	11.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
3	1	11.1%
9	1	11.1%

NONLIVINGAREA_AVG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	571.0 B

0.0098	1
0.0	1

Length

Max length	6
Median length	4.5
Mean length	4.5
Min length	3

Characters and Unicode

Total characters	9
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0
2nd row	0.0098

Common Values

Value	Count	Frequency (%)
0.0098	1	10.0%
0.0	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	1	50.0%
0.0098	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
9	1	11.1%
8	1	11.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	7	77.8%
Other Punctuation	2	22.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	71.4%
9	1	14.3%
8	1	14.3%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	9	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
9	1	11.1%
8	1	11.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
9	1	11.1%
8	1	11.1%

APARTMENTS_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0252	1
0.0924	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0252
2nd row	0.0924

Common Values

Value	Count	Frequency (%)
0.0252	1	10.0%
0.0924	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0924	1	50.0%
0.0252	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
2	3	25.0%
.	2	16.7%
5	1	8.3%
9	1	8.3%
4	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
2	3	30.0%
5	1	10.0%
9	1	10.0%
4	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
2	3	25.0%
.	2	16.7%
5	1	8.3%
9	1	8.3%
4	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
2	3	25.0%
.	2	16.7%
5	1	8.3%
9	1	8.3%
4	1	8.3%

BASEMENTAREA_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0538	1
0.0383	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0383
2nd row	0.0538

Common Values

Value	Count	Frequency (%)
0.0538	1	10.0%
0.0383	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0383	1	50.0%
0.0538	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
3	3	25.0%
.	2	16.7%
8	2	16.7%
5	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
3	3	30.0%
8	2	20.0%
5	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
3	3	25.0%
.	2	16.7%
8	2	16.7%
5	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
3	3	25.0%
.	2	16.7%
8	2	16.7%
5	1	8.3%

YEARS_BEGINEXPLUATATION_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.9851	1
0.9722	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.9722
2nd row	0.9851

Common Values

Value	Count	Frequency (%)
0.9851	1	10.0%
0.9722	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.9722	1	50.0%
0.9851	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
9	2	16.7%
2	2	16.7%
7	1	8.3%
8	1	8.3%
5	1	8.3%
1	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	2	20.0%
9	2	20.0%
2	2	20.0%
7	1	10.0%
8	1	10.0%
5	1	10.0%
1	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
9	2	16.7%
2	2	16.7%
7	1	8.3%
8	1	8.3%
5	1	8.3%
1	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
9	2	16.7%
2	2	16.7%
7	1	8.3%
8	1	8.3%
5	1	8.3%
1	1	8.3%

YEARS_BUILD_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	573.0 B

0.6341	1
0.804	1

Length

Max length	6
Median length	5.5
Mean length	5.5
Min length	5

Characters and Unicode

Total characters	11
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.6341
2nd row	0.804

Common Values

Value	Count	Frequency (%)
0.6341	1	10.0%
0.804	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.804	1	50.0%
0.6341	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	3	27.3%
.	2	18.2%
4	2	18.2%
6	1	9.1%
3	1	9.1%
1	1	9.1%
8	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9	81.8%
Other Punctuation	2	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3	33.3%
4	2	22.2%
6	1	11.1%
3	1	11.1%
1	1	11.1%
8	1	11.1%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3	27.3%
.	2	18.2%
4	2	18.2%
6	1	9.1%
3	1	9.1%
1	1	9.1%
8	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3	27.3%
.	2	18.2%
4	2	18.2%
6	1	9.1%
3	1	9.1%
1	1	9.1%
8	1	9.1%

COMMONAREA_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0144	1
0.0497	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0144
2nd row	0.0497

Common Values

Value	Count	Frequency (%)
0.0144	1	10.0%
0.0497	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0497	1	50.0%
0.0144	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
4	3	25.0%
.	2	16.7%
1	1	8.3%
9	1	8.3%
7	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
4	3	30.0%
1	1	10.0%
9	1	10.0%
7	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
4	3	25.0%
.	2	16.7%
1	1	8.3%
9	1	8.3%
7	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
4	3	25.0%
.	2	16.7%
1	1	8.3%
9	1	8.3%
7	1	8.3%

ELEVATORS_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	571.0 B

0.0	1
0.0806	1

Length

Max length	6
Median length	4.5
Mean length	4.5
Min length	3

Characters and Unicode

Total characters	9
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0
2nd row	0.0806

Common Values

Value	Count	Frequency (%)
0.0	1	10.0%
0.0806	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0806	1	50.0%
0.0	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
8	1	11.1%
6	1	11.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	7	77.8%
Other Punctuation	2	22.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	71.4%
8	1	14.3%
6	1	14.3%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	9	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
8	1	11.1%
6	1	11.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
8	1	11.1%
6	1	11.1%

ENTRANCES_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	573.0 B

0.069	1
0.0345	1

Length

Max length	6
Median length	5.5
Mean length	5.5
Min length	5

Characters and Unicode

Total characters	11
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.069
2nd row	0.0345

Common Values

Value	Count	Frequency (%)
0.069	1	10.0%
0.0345	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0345	1	50.0%
0.069	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
6	1	9.1%
9	1	9.1%
3	1	9.1%
4	1	9.1%
5	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9	81.8%
Other Punctuation	2	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	44.4%
6	1	11.1%
9	1	11.1%
3	1	11.1%
4	1	11.1%
5	1	11.1%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
6	1	9.1%
9	1	9.1%
3	1	9.1%
4	1	9.1%
5	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
6	1	9.1%
9	1	9.1%
3	1	9.1%
4	1	9.1%
5	1	9.1%

FLOORSMAX_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0833	1
0.2917	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0833
2nd row	0.2917

Common Values

Value	Count	Frequency (%)
0.0833	1	10.0%
0.2917	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.2917	1	50.0%
0.0833	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	3	25.0%
.	2	16.7%
3	2	16.7%
8	1	8.3%
2	1	8.3%
9	1	8.3%
1	1	8.3%
7	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3	30.0%
3	2	20.0%
8	1	10.0%
2	1	10.0%
9	1	10.0%
1	1	10.0%
7	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3	25.0%
.	2	16.7%
3	2	16.7%
8	1	8.3%
2	1	8.3%
9	1	8.3%
1	1	8.3%
7	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3	25.0%
.	2	16.7%
3	2	16.7%
8	1	8.3%
2	1	8.3%
9	1	8.3%
1	1	8.3%
7	1	8.3%

FLOORSMIN_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	573.0 B

0.3333	1
0.125	1

Length

Max length	6
Median length	5.5
Mean length	5.5
Min length	5

Characters and Unicode

Total characters	11
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.125
2nd row	0.3333

Common Values

Value	Count	Frequency (%)
0.3333	1	10.0%
0.125	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.125	1	50.0%
0.3333	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
3	4	36.4%
0	2	18.2%
.	2	18.2%
1	1	9.1%
2	1	9.1%
5	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9	81.8%
Other Punctuation	2	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	4	44.4%
0	2	22.2%
1	1	11.1%
2	1	11.1%
5	1	11.1%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	4	36.4%
0	2	18.2%
.	2	18.2%
1	1	9.1%
2	1	9.1%
5	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	4	36.4%
0	2	18.2%
.	2	18.2%
1	1	9.1%
2	1	9.1%
5	1	9.1%

LANDAREA_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0377	1
0.0128	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0377
2nd row	0.0128

Common Values

Value	Count	Frequency (%)
0.0377	1	10.0%
0.0128	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0128	1	50.0%
0.0377	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
7	2	16.7%
3	1	8.3%
1	1	8.3%
2	1	8.3%
8	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
7	2	20.0%
3	1	10.0%
1	1	10.0%
2	1	10.0%
8	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
7	2	16.7%
3	1	8.3%
1	1	8.3%
2	1	8.3%
8	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
7	2	16.7%
3	1	8.3%
1	1	8.3%
2	1	8.3%
8	1	8.3%

LIVINGAPARTMENTS_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	587.0 B

0.079	1
0.022000000000000002	1

Length

Max length	20
Median length	12.5
Mean length	12.5
Min length	5

Characters and Unicode

Total characters	25
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.022000000000000002
2nd row	0.079

Common Values

Value	Count	Frequency (%)
0.079	1	10.0%
0.022000000000000002	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.022000000000000002	1	50.0%
0.079	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	18	72.0%
2	3	12.0%
.	2	8.0%
7	1	4.0%
9	1	4.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	23	92.0%
Other Punctuation	2	8.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	18	78.3%
2	3	13.0%
7	1	4.3%
9	1	4.3%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	25	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	18	72.0%
2	3	12.0%
.	2	8.0%
7	1	4.0%
9	1	4.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	25	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	18	72.0%
2	3	12.0%
.	2	8.0%
7	1	4.0%
9	1	4.0%

LIVINGAREA_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0198	1
0.0554	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0198
2nd row	0.0554

Common Values

Value	Count	Frequency (%)
0.0198	1	10.0%
0.0554	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0554	1	50.0%
0.0198	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
5	2	16.7%
1	1	8.3%
9	1	8.3%
8	1	8.3%
4	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
5	2	20.0%
1	1	10.0%
9	1	10.0%
8	1	10.0%
4	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
5	2	16.7%
1	1	8.3%
9	1	8.3%
8	1	8.3%
4	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
5	2	16.7%
1	1	8.3%
9	1	8.3%
8	1	8.3%
4	1	8.3%

NONLIVINGAPARTMENTS_MODE
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	50.0%
Missing	8
Missing (%)	80.0%
Memory size	568.0 B

0.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	6
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0

Common Values

Value	Count	Frequency (%)
0.0	2	20.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	66.7%
.	2	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4	66.7%
Other Punctuation	2	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	6	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	66.7%
.	2	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	66.7%
.	2	33.3%

NONLIVINGAREA_MODE
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	50.0%
Missing	8
Missing (%)	80.0%
Memory size	568.0 B

0.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	6
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0

Common Values

Value	Count	Frequency (%)
0.0	2	20.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	2	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	66.7%
.	2	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4	66.7%
Other Punctuation	2	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	6	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	66.7%
.	2	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	66.7%
.	2	33.3%

APARTMENTS_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	573.0 B

0.025	1
0.0968	1

Length

Max length	6
Median length	5.5
Mean length	5.5
Min length	5

Characters and Unicode

Total characters	11
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.025
2nd row	0.0968

Common Values

Value	Count	Frequency (%)
0.025	1	10.0%
0.0968	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0968	1	50.0%
0.025	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
2	1	9.1%
5	1	9.1%
9	1	9.1%
6	1	9.1%
8	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9	81.8%
Other Punctuation	2	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	44.4%
2	1	11.1%
5	1	11.1%
9	1	11.1%
6	1	11.1%
8	1	11.1%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
2	1	9.1%
5	1	9.1%
9	1	9.1%
6	1	9.1%
8	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
2	1	9.1%
5	1	9.1%
9	1	9.1%
6	1	9.1%
8	1	9.1%

BASEMENTAREA_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0369	1
0.0529	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0369
2nd row	0.0529

Common Values

Value	Count	Frequency (%)
0.0369	1	10.0%
0.0529	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0529	1	50.0%
0.0369	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
9	2	16.7%
3	1	8.3%
6	1	8.3%
5	1	8.3%
2	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
9	2	20.0%
3	1	10.0%
6	1	10.0%
5	1	10.0%
2	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
9	2	16.7%
3	1	8.3%
6	1	8.3%
5	1	8.3%
2	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
9	2	16.7%
3	1	8.3%
6	1	8.3%
5	1	8.3%
2	1	8.3%

YEARS_BEGINEXPLUATATION_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.9851	1
0.9722	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.9722
2nd row	0.9851

Common Values

Value	Count	Frequency (%)
0.9851	1	10.0%
0.9722	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.9722	1	50.0%
0.9851	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
9	2	16.7%
2	2	16.7%
7	1	8.3%
8	1	8.3%
5	1	8.3%
1	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	2	20.0%
9	2	20.0%
2	2	20.0%
7	1	10.0%
8	1	10.0%
5	1	10.0%
1	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
9	2	16.7%
2	2	16.7%
7	1	8.3%
8	1	8.3%
5	1	8.3%
1	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
9	2	16.7%
2	2	16.7%
7	1	8.3%
8	1	8.3%
5	1	8.3%
1	1	8.3%

YEARS_BUILD_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.6243	1
0.7987	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	9
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.6243
2nd row	0.7987

Common Values

Value	Count	Frequency (%)
0.6243	1	10.0%
0.7987	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.7987	1	50.0%
0.6243	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
7	2	16.7%
6	1	8.3%
2	1	8.3%
4	1	8.3%
3	1	8.3%
9	1	8.3%
8	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	2	20.0%
7	2	20.0%
6	1	10.0%
2	1	10.0%
4	1	10.0%
3	1	10.0%
9	1	10.0%
8	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
7	2	16.7%
6	1	8.3%
2	1	8.3%
4	1	8.3%
3	1	8.3%
9	1	8.3%
8	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	2	16.7%
.	2	16.7%
7	2	16.7%
6	1	8.3%
2	1	8.3%
4	1	8.3%
3	1	8.3%
9	1	8.3%
8	1	8.3%

COMMONAREA_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0144	1
0.0608	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0144
2nd row	0.0608

Common Values

Value	Count	Frequency (%)
0.0144	1	10.0%
0.0608	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0608	1	50.0%
0.0144	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
4	2	16.7%
1	1	8.3%
6	1	8.3%
8	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	50.0%
4	2	20.0%
1	1	10.0%
6	1	10.0%
8	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
4	2	16.7%
1	1	8.3%
6	1	8.3%
8	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
4	2	16.7%
1	1	8.3%
6	1	8.3%
8	1	8.3%

ELEVATORS_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	569.0 B

0.08	1
0.0	1

Length

Max length	4
Median length	3.5
Mean length	3.5
Min length	3

Characters and Unicode

Total characters	7
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0
2nd row	0.08

Common Values

Value	Count	Frequency (%)
0.08	1	10.0%
0.0	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	1	50.0%
0.08	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	57.1%
.	2	28.6%
8	1	14.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5	71.4%
Other Punctuation	2	28.6%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	80.0%
8	1	20.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	7	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	57.1%
.	2	28.6%
8	1	14.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	57.1%
.	2	28.6%
8	1	14.3%

ENTRANCES_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	573.0 B

0.069	1
0.0345	1

Length

Max length	6
Median length	5.5
Mean length	5.5
Min length	5

Characters and Unicode

Total characters	11
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.069
2nd row	0.0345

Common Values

Value	Count	Frequency (%)
0.069	1	10.0%
0.0345	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0345	1	50.0%
0.069	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
6	1	9.1%
9	1	9.1%
3	1	9.1%
4	1	9.1%
5	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9	81.8%
Other Punctuation	2	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	44.4%
6	1	11.1%
9	1	11.1%
3	1	11.1%
4	1	11.1%
5	1	11.1%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
6	1	9.1%
9	1	9.1%
3	1	9.1%
4	1	9.1%
5	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	36.4%
.	2	18.2%
6	1	9.1%
9	1	9.1%
3	1	9.1%
4	1	9.1%
5	1	9.1%

FLOORSMAX_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0833	1
0.2917	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0833
2nd row	0.2917

Common Values

Value	Count	Frequency (%)
0.0833	1	10.0%
0.2917	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.2917	1	50.0%
0.0833	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	3	25.0%
.	2	16.7%
3	2	16.7%
8	1	8.3%
2	1	8.3%
9	1	8.3%
1	1	8.3%
7	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3	30.0%
3	2	20.0%
8	1	10.0%
2	1	10.0%
9	1	10.0%
1	1	10.0%
7	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3	25.0%
.	2	16.7%
3	2	16.7%
8	1	8.3%
2	1	8.3%
9	1	8.3%
1	1	8.3%
7	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3	25.0%
.	2	16.7%
3	2	16.7%
8	1	8.3%
2	1	8.3%
9	1	8.3%
1	1	8.3%
7	1	8.3%

FLOORSMIN_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	573.0 B

0.3333	1
0.125	1

Length

Max length	6
Median length	5.5
Mean length	5.5
Min length	5

Characters and Unicode

Total characters	11
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.125
2nd row	0.3333

Common Values

Value	Count	Frequency (%)
0.3333	1	10.0%
0.125	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.125	1	50.0%
0.3333	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
3	4	36.4%
0	2	18.2%
.	2	18.2%
1	1	9.1%
2	1	9.1%
5	1	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9	81.8%
Other Punctuation	2	18.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	4	44.4%
0	2	22.2%
1	1	11.1%
2	1	11.1%
5	1	11.1%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	4	36.4%
0	2	18.2%
.	2	18.2%
1	1	9.1%
2	1	9.1%
5	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	4	36.4%
0	2	18.2%
.	2	18.2%
1	1	9.1%
2	1	9.1%
5	1	9.1%

LANDAREA_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0132	1
0.0375	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0375
2nd row	0.0132

Common Values

Value	Count	Frequency (%)
0.0132	1	10.0%
0.0375	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0375	1	50.0%
0.0132	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
3	2	16.7%
7	1	8.3%
5	1	8.3%
1	1	8.3%
2	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
3	2	20.0%
7	1	10.0%
5	1	10.0%
1	1	10.0%
2	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
3	2	16.7%
7	1	8.3%
5	1	8.3%
1	1	8.3%
2	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
3	2	16.7%
7	1	8.3%
5	1	8.3%
1	1	8.3%
2	1	8.3%

LIVINGAPARTMENTS_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0787	1
0.0205	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0205
2nd row	0.0787

Common Values

Value	Count	Frequency (%)
0.0787	1	10.0%
0.0205	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0205	1	50.0%
0.0787	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
7	2	16.7%
2	1	8.3%
5	1	8.3%
8	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	50.0%
7	2	20.0%
2	1	10.0%
5	1	10.0%
8	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
7	2	16.7%
2	1	8.3%
5	1	8.3%
8	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5	41.7%
.	2	16.7%
7	2	16.7%
2	1	8.3%
5	1	8.3%
8	1	8.3%

LIVINGAREA_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0193	1
0.0558	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0193
2nd row	0.0558

Common Values

Value	Count	Frequency (%)
0.0193	1	10.0%
0.0558	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0558	1	50.0%
0.0193	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
5	2	16.7%
1	1	8.3%
9	1	8.3%
3	1	8.3%
8	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
5	2	20.0%
1	1	10.0%
9	1	10.0%
3	1	10.0%
8	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
5	2	16.7%
1	1	8.3%
9	1	8.3%
3	1	8.3%
8	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
5	2	16.7%
1	1	8.3%
9	1	8.3%
3	1	8.3%
8	1	8.3%

NONLIVINGAPARTMENTS_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	571.0 B

0.0039	1
0.0	1

Length

Max length	6
Median length	4.5
Mean length	4.5
Min length	3

Characters and Unicode

Total characters	9
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0
2nd row	0.0039

Common Values

Value	Count	Frequency (%)
0.0039	1	10.0%
0.0	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	1	50.0%
0.0039	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
3	1	11.1%
9	1	11.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	7	77.8%
Other Punctuation	2	22.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	71.4%
3	1	14.3%
9	1	14.3%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	9	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
3	1	11.1%
9	1	11.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5	55.6%
.	2	22.2%
3	1	11.1%
9	1	11.1%

NONLIVINGAREA_MEDI
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	569.0 B

0.01	1
0.0	1

Length

Max length	4
Median length	3.5
Mean length	3.5
Min length	3

Characters and Unicode

Total characters	7
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0
2nd row	0.01

Common Values

Value	Count	Frequency (%)
0.01	1	10.0%
0.0	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	1	50.0%
0.01	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	57.1%
.	2	28.6%
1	1	14.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5	71.4%
Other Punctuation	2	28.6%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	80.0%
1	1	20.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	7	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	57.1%
.	2	28.6%
1	1	14.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	57.1%
.	2	28.6%
1	1	14.3%

FONDKAPREMONT_MODE
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	50.0%
Missing	8
Missing (%)	80.0%
Memory size	530.0 B

reg oper account	2

Length

Max length	16
Median length	16
Mean length	16
Min length	16

Characters and Unicode

Total characters	32
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	reg oper account
2nd row	reg oper account

Common Values

Value	Count	Frequency (%)
reg oper account	2	20.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
account	2	33.3%
oper	2	33.3%
reg	2	33.3%

Most occurring characters

Value	Count	Frequency (%)
r	4	12.5%
e	4	12.5%
	4	12.5%
o	4	12.5%
c	4	12.5%
g	2	6.2%
p	2	6.2%
a	2	6.2%
u	2	6.2%
n	2	6.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	28	87.5%
Space Separator	4	12.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	4	14.3%
e	4	14.3%
o	4	14.3%
c	4	14.3%
g	2	7.1%
p	2	7.1%
a	2	7.1%
u	2	7.1%
n	2	7.1%
t	2	7.1%

Space Separator

Value	Count	Frequency (%)
	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	28	87.5%
Common	4	12.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	4	14.3%
e	4	14.3%
o	4	14.3%
c	4	14.3%
g	2	7.1%
p	2	7.1%
a	2	7.1%
u	2	7.1%
n	2	7.1%
t	2	7.1%

Common

Value	Count	Frequency (%)
	4	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	32	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	4	12.5%
e	4	12.5%
	4	12.5%
o	4	12.5%
c	4	12.5%
g	2	6.2%
p	2	6.2%
a	2	6.2%
u	2	6.2%
n	2	6.2%

HOUSETYPE_MODE
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	50.0%
Missing	8
Missing (%)	80.0%
Memory size	526.0 B

block of flats	2

Length

Max length	14
Median length	14
Mean length	14
Min length	14

Characters and Unicode

Total characters	28
Distinct characters	10
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	block of flats
2nd row	block of flats

Common Values

Value	Count	Frequency (%)
block of flats	2	20.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
of	2	33.3%
flats	2	33.3%
block	2	33.3%

Most occurring characters

Value	Count	Frequency (%)
l	4	14.3%
o	4	14.3%
	4	14.3%
f	4	14.3%
b	2	7.1%
c	2	7.1%
k	2	7.1%
a	2	7.1%
t	2	7.1%
s	2	7.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	24	85.7%
Space Separator	4	14.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	4	16.7%
o	4	16.7%
f	4	16.7%
b	2	8.3%
c	2	8.3%
k	2	8.3%
a	2	8.3%
t	2	8.3%
s	2	8.3%

Space Separator

Value	Count	Frequency (%)
	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	24	85.7%
Common	4	14.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
l	4	16.7%
o	4	16.7%
f	4	16.7%
b	2	8.3%
c	2	8.3%
k	2	8.3%
a	2	8.3%
t	2	8.3%
s	2	8.3%

Common

Value	Count	Frequency (%)
	4	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	28	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
l	4	14.3%
o	4	14.3%
	4	14.3%
f	4	14.3%
b	2	7.1%
c	2	7.1%
k	2	7.1%
a	2	7.1%
t	2	7.1%
s	2	7.1%

TOTALAREA_MODE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	574.0 B

0.0149	1
0.0714	1

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	12
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	0.0149
2nd row	0.0714

Common Values

Value	Count	Frequency (%)
0.0149	1	10.0%
0.0714	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0714	1	50.0%
0.0149	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
1	2	16.7%
4	2	16.7%
9	1	8.3%
7	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	83.3%
Other Punctuation	2	16.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	40.0%
1	2	20.0%
4	2	20.0%
9	1	10.0%
7	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
1	2	16.7%
4	2	16.7%
9	1	8.3%
7	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4	33.3%
.	2	16.7%
1	2	16.7%
4	2	16.7%
9	1	8.3%
7	1	8.3%

WALLSMATERIAL_MODE
Categorical

MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	8
Missing (%)	80.0%
Memory size	515.0 B

Block	1
Stone, brick	1

Length

Max length	12
Median length	8.5
Mean length	8.5
Min length	5

Characters and Unicode

Total characters	17
Distinct characters	14
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	Stone, brick
2nd row	Block

Common Values

Value	Count	Frequency (%)
Block	1	10.0%
Stone, brick	1	10.0%
(Missing)	8	80.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
brick	1	33.3%
block	1	33.3%
stone	1	33.3%

Most occurring characters

Value	Count	Frequency (%)
o	2	11.8%
c	2	11.8%
k	2	11.8%
S	1	5.9%
t	1	5.9%
n	1	5.9%
e	1	5.9%
,	1	5.9%
	1	5.9%
b	1	5.9%
Other values (4)	4	23.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	13	76.5%
Uppercase Letter	2	11.8%
Other Punctuation	1	5.9%
Space Separator	1	5.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	2	15.4%
c	2	15.4%
k	2	15.4%
t	1	7.7%
n	1	7.7%
e	1	7.7%
b	1	7.7%
r	1	7.7%
i	1	7.7%
l	1	7.7%

Uppercase Letter

Value	Count	Frequency (%)
S	1	50.0%
B	1	50.0%

Other Punctuation

Value	Count	Frequency (%)
,	1	100.0%

Space Separator

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	15	88.2%
Common	2	11.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	2	13.3%
c	2	13.3%
k	2	13.3%
S	1	6.7%
t	1	6.7%
n	1	6.7%
e	1	6.7%
b	1	6.7%
r	1	6.7%
i	1	6.7%
Other values (2)	2	13.3%

Common

Value	Count	Frequency (%)
,	1	50.0%
	1	50.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	17	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	2	11.8%
c	2	11.8%
k	2	11.8%
S	1	5.9%
t	1	5.9%
n	1	5.9%
e	1	5.9%
,	1	5.9%
	1	5.9%
b	1	5.9%
Other values (4)	4	23.5%

EMERGENCYSTATE_MODE
Boolean

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	50.0%
Missing	8
Missing (%)	80.0%
Memory size	148.0 B

False	2
(Missing)	8

Common Values
Chart

Value	Count	Frequency (%)
False	2	20.0%
(Missing)	8	80.0%

OBS_30_CNT_SOCIAL_CIRCLE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	30.0%
Missing	0
Missing (%)	0.0%
Memory size	728.0 B

2.0	4
1.0	3
0.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	30
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	0.0
4th row	2.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
2.0	4	40.0%
1.0	3	30.0%
0.0	3	30.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	4	40.0%
0.0	3	30.0%
1.0	3	30.0%

Most occurring characters

Value	Count	Frequency (%)
0	13	43.3%
.	10	33.3%
2	4	13.3%
1	3	10.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	20	66.7%
Other Punctuation	10	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	13	65.0%
2	4	20.0%
1	3	15.0%

Other Punctuation

Value	Count	Frequency (%)
.	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	13	43.3%
.	10	33.3%
2	4	13.3%
1	3	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	13	43.3%
.	10	33.3%
2	4	13.3%
1	3	10.0%

DEF_30_CNT_SOCIAL_CIRCLE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	728.0 B

0.0	9
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	30
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	10.0%

Sample

1st row	2.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	9	90.0%
2.0	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	9	90.0%
2.0	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
0	19	63.3%
.	10	33.3%
2	1	3.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	20	66.7%
Other Punctuation	10	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	19	95.0%
2	1	5.0%

Other Punctuation

Value	Count	Frequency (%)
.	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	19	63.3%
.	10	33.3%
2	1	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	19	63.3%
.	10	33.3%
2	1	3.3%

OBS_60_CNT_SOCIAL_CIRCLE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	30.0%
Missing	0
Missing (%)	0.0%
Memory size	728.0 B

2.0	4
1.0	3
0.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	30
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	0.0
4th row	2.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
2.0	4	40.0%
1.0	3	30.0%
0.0	3	30.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	4	40.0%
0.0	3	30.0%
1.0	3	30.0%

Most occurring characters

Value	Count	Frequency (%)
0	13	43.3%
.	10	33.3%
2	4	13.3%
1	3	10.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	20	66.7%
Other Punctuation	10	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	13	65.0%
2	4	20.0%
1	3	15.0%

Other Punctuation

Value	Count	Frequency (%)
.	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	13	43.3%
.	10	33.3%
2	4	13.3%
1	3	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	13	43.3%
.	10	33.3%
2	4	13.3%
1	3	10.0%

DEF_60_CNT_SOCIAL_CIRCLE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	728.0 B

0.0	9
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	30
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	10.0%

Sample

1st row	2.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	9	90.0%
2.0	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	9	90.0%
2.0	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
0	19	63.3%
.	10	33.3%
2	1	3.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	20	66.7%
Other Punctuation	10	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	19	95.0%
2	1	5.0%

Other Punctuation

Value	Count	Frequency (%)
.	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	19	63.3%
.	10	33.3%
2	1	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	19	63.3%
.	10	33.3%
2	1	3.3%

DAYS_LAST_PHONE_CHANGE
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE
ZEROS

Distinct	10
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-1134.1

Minimum	-2536
Maximum	0
Zeros	1
Zeros (%)	10.0%
Negative	9
Negative (%)	90.0%
Memory size	208.0 B

Quantile statistics

Minimum	-2536
5-th percentile	-2147.65
Q1	-1455
median	-1088
Q3	-818.25
95-th percentile	-277.65
Maximum	0
Range	2536
Interquartile range (IQR)	636.75

Descriptive statistics

Standard deviation	682.546775
Coefficient of variation (CV)	-0.6018400273
Kurtosis	1.418163117
Mean	-1134.1
Median Absolute Deviation (MAD)	372
Skewness	-0.5816488087
Sum	-11341
Variance	465870.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
-1673	1	10.0%
0	1	10.0%
-1070	1	10.0%
-1562	1	10.0%
-2536	1	10.0%
-1106	1	10.0%
-617	1	10.0%
-815	1	10.0%
-828	1	10.0%
-1134	1	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2536	1	10.0%
-1673	1	10.0%
-1562	1	10.0%
-1134	1	10.0%
-1106	1	10.0%
-1070	1	10.0%
-828	1	10.0%
-815	1	10.0%
-617	1	10.0%
0	1	10.0%

Value	Count	Frequency (%)
0	1	10.0%
-617	1	10.0%
-815	1	10.0%
-828	1	10.0%
-1070	1	10.0%
-1106	1	10.0%
-1134	1	10.0%
-1562	1	10.0%
-1673	1	10.0%
-2536	1	10.0%

FLAG_DOCUMENT_2
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

1	6
0	4

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	6	60.0%
0	4	40.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	6	60.0%
0	4	40.0%

Most occurring characters

Value	Count	Frequency (%)
1	6	60.0%
0	4	40.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	6	60.0%
0	4	40.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	6	60.0%
0	4	40.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	6	60.0%
0	4	40.0%

FLAG_DOCUMENT_4
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_5
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_6
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_7
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_8
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	8
1	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring characters

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	8	80.0%
1	2	20.0%

FLAG_DOCUMENT_9
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_10
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_11
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_12
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_13
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_14
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	9
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	10.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring characters

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	9	90.0%
1	1	10.0%

FLAG_DOCUMENT_15
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_16
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_17
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_18
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_19
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_20
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

FLAG_DOCUMENT_21
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	708.0 B

0	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	10	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	10	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	10	100.0%

AMT_REQ_CREDIT_BUREAU_HOUR
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	12.5%
Missing	2
Missing (%)	20.0%
Memory size	688.0 B

0.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	24
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8	80.0%
(Missing)	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	16	66.7%
.	8	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	16	66.7%
Other Punctuation	8	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	16	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	8	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	24	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	16	66.7%
.	8	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	16	66.7%
.	8	33.3%

AMT_REQ_CREDIT_BUREAU_DAY
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	12.5%
Missing	2
Missing (%)	20.0%
Memory size	688.0 B

0.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	24
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8	80.0%
(Missing)	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	16	66.7%
.	8	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	16	66.7%
Other Punctuation	8	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	16	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	8	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	24	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	16	66.7%
.	8	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	16	66.7%
.	8	33.3%

AMT_REQ_CREDIT_BUREAU_WEEK
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	12.5%
Missing	2
Missing (%)	20.0%
Memory size	688.0 B

0.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	24
Distinct characters	2
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8	80.0%
(Missing)	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	16	66.7%
.	8	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	16	66.7%
Other Punctuation	8	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	16	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	8	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	24	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	16	66.7%
.	8	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	16	66.7%
.	8	33.3%

AMT_REQ_CREDIT_BUREAU_MON
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	25.0%
Missing	2
Missing (%)	20.0%
Memory size	688.0 B

0.0	7
1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	24
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	12.5%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7	70.0%
1.0	1	10.0%
(Missing)	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7	87.5%
1.0	1	12.5%

Most occurring characters

Value	Count	Frequency (%)
0	15	62.5%
.	8	33.3%
1	1	4.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	16	66.7%
Other Punctuation	8	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	15	93.8%
1	1	6.2%

Other Punctuation

Value	Count	Frequency (%)
.	8	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	24	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	15	62.5%
.	8	33.3%
1	1	4.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	15	62.5%
.	8	33.3%
1	1	4.2%

AMT_REQ_CREDIT_BUREAU_QRT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	25.0%
Missing	2
Missing (%)	20.0%
Memory size	688.0 B

0.0	6
1.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	24
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	6	60.0%
1.0	2	20.0%
(Missing)	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	6	75.0%
1.0	2	25.0%

Most occurring characters

Value	Count	Frequency (%)
0	14	58.3%
.	8	33.3%
1	2	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	16	66.7%
Other Punctuation	8	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	14	87.5%
1	2	12.5%

Other Punctuation

Value	Count	Frequency (%)
.	8	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	24	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	14	58.3%
.	8	33.3%
1	2	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	14	58.3%
.	8	33.3%
1	2	8.3%

AMT_REQ_CREDIT_BUREAU_YEAR
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	37.5%
Missing	2
Missing (%)	20.0%
Memory size	688.0 B

0.0	4
1.0	3
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	24
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	12.5%

Sample

1st row	1.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	4	40.0%
1.0	3	30.0%
2.0	1	10.0%
(Missing)	2	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	4	50.0%
1.0	3	37.5%
2.0	1	12.5%

Most occurring characters

Value	Count	Frequency (%)
0	12	50.0%
.	8	33.3%
1	3	12.5%
2	1	4.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	16	66.7%
Other Punctuation	8	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	12	75.0%
1	3	18.8%
2	1	6.2%

Other Punctuation

Value	Count	Frequency (%)
.	8	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	24	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	12	50.0%
.	8	33.3%
1	3	12.5%
2	1	4.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	12	50.0%
.	8	33.3%
1	3	12.5%
2	1	4.2%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	SK_ID_CURR	TARGET	NAME_CONTRACT_TYPE	CODE_GENDER	FLAG_OWN_CAR	FLAG_OWN_REALTY	CNT_CHILDREN	AMT_INCOME_TOTAL	AMT_CREDIT	AMT_ANNUITY	AMT_GOODS_PRICE	NAME_TYPE_SUITE	NAME_INCOME_TYPE	NAME_EDUCATION_TYPE	NAME_FAMILY_STATUS	NAME_HOUSING_TYPE	REGION_POPULATION_RELATIVE	DAYS_BIRTH	DAYS_EMPLOYED	DAYS_REGISTRATION	DAYS_ID_PUBLISH	OWN_CAR_AGE	FLAG_MOBIL	FLAG_EMP_PHONE	FLAG_WORK_PHONE	FLAG_CONT_MOBILE	FLAG_PHONE	OCCUPATION_TYPE	CNT_FAM_MEMBERS	REGION_RATING_CLIENT	REGION_RATING_CLIENT_W_CITY	WEEKDAY_APPR_PROCESS_START	HOUR_APPR_PROCESS_START	REG_CITY_NOT_WORK_CITY	LIVE_CITY_NOT_WORK_CITY	ORGANIZATION_TYPE	EXT_SOURCE_1	EXT_SOURCE_2	EXT_SOURCE_3	APARTMENTS_AVG	BASEMENTAREA_AVG	YEARS_BEGINEXPLUATATION_AVG	YEARS_BUILD_AVG	COMMONAREA_AVG	ELEVATORS_AVG	ENTRANCES_AVG	FLOORSMAX_AVG	FLOORSMIN_AVG	LANDAREA_AVG	LIVINGAPARTMENTS_AVG	LIVINGAREA_AVG	NONLIVINGAPARTMENTS_AVG	NONLIVINGAREA_AVG	APARTMENTS_MODE	BASEMENTAREA_MODE	YEARS_BEGINEXPLUATATION_MODE	YEARS_BUILD_MODE	COMMONAREA_MODE	ELEVATORS_MODE	ENTRANCES_MODE	FLOORSMAX_MODE	FLOORSMIN_MODE	LANDAREA_MODE	LIVINGAPARTMENTS_MODE	LIVINGAREA_MODE	NONLIVINGAPARTMENTS_MODE	NONLIVINGAREA_MODE	APARTMENTS_MEDI	BASEMENTAREA_MEDI	YEARS_BEGINEXPLUATATION_MEDI	YEARS_BUILD_MEDI	COMMONAREA_MEDI	ELEVATORS_MEDI	ENTRANCES_MEDI	FLOORSMAX_MEDI	FLOORSMIN_MEDI	LANDAREA_MEDI	LIVINGAPARTMENTS_MEDI	LIVINGAREA_MEDI	NONLIVINGAPARTMENTS_MEDI	NONLIVINGAREA_MEDI	FONDKAPREMONT_MODE	HOUSETYPE_MODE	TOTALAREA_MODE	WALLSMATERIAL_MODE	EMERGENCYSTATE_MODE	OBS_30_CNT_SOCIAL_CIRCLE	DEF_30_CNT_SOCIAL_CIRCLE	OBS_60_CNT_SOCIAL_CIRCLE	DEF_60_CNT_SOCIAL_CIRCLE	DAYS_LAST_PHONE_CHANGE	FLAG_DOCUMENT_3	FLAG_DOCUMENT_8	FLAG_DOCUMENT_14	AMT_REQ_CREDIT_BUREAU_HOUR	AMT_REQ_CREDIT_BUREAU_DAY	AMT_REQ_CREDIT_BUREAU_WEEK	AMT_REQ_CREDIT_BUREAU_MON	AMT_REQ_CREDIT_BUREAU_QRT	AMT_REQ_CREDIT_BUREAU_YEAR
0	100002	1	Cash loans	M	N	Y	0	202500.0	406597.5	24700.5	351000.0	Unaccompanied	Working	Secondary / secondary special	Single / not married	House / apartment	0.018801	-9461	-637	-3648.0	-2120	NaN	1	1	0	1	1	Laborers	1.0	2	2	WEDNESDAY	10	0	0	Business Entity Type 3	0.083037	0.262949	0.139376	0.0247	0.0369	0.9722	0.6192	0.0143	0.00	0.0690	0.0833	0.1250	0.0369	0.0202	0.0190	0.0000	0.0000	0.0252	0.0383	0.9722	0.6341	0.0144	0.0000	0.0690	0.0833	0.1250	0.0377	0.022	0.0198	0.0	0.0	0.0250	0.0369	0.9722	0.6243	0.0144	0.00	0.0690	0.0833	0.1250	0.0375	0.0205	0.0193	0.0000	0.00	reg oper account	block of flats	0.0149	Stone, brick	No	2.0	2.0	2.0	2.0	-1134.0	1	0	0	0.0	0.0	0.0	0.0	0.0	1.0
1	100003	0	Cash loans	F	N	N	0	270000.0	1293502.5	35698.5	1129500.0	Family	State servant	Higher education	Married	House / apartment	0.003541	-16765	-1188	-1186.0	-291	NaN	1	1	0	1	1	Core staff	2.0	1	1	MONDAY	11	0	0	School	0.311267	0.622246	NaN	0.0959	0.0529	0.9851	0.7960	0.0605	0.08	0.0345	0.2917	0.3333	0.0130	0.0773	0.0549	0.0039	0.0098	0.0924	0.0538	0.9851	0.8040	0.0497	0.0806	0.0345	0.2917	0.3333	0.0128	0.079	0.0554	0.0	0.0	0.0968	0.0529	0.9851	0.7987	0.0608	0.08	0.0345	0.2917	0.3333	0.0132	0.0787	0.0558	0.0039	0.01	reg oper account	block of flats	0.0714	Block	No	1.0	0.0	1.0	0.0	-828.0	1	0	0	0.0	0.0	0.0	0.0	0.0	0.0
2	100004	0	Revolving loans	M	Y	Y	0	67500.0	135000.0	6750.0	135000.0	Unaccompanied	Working	Secondary / secondary special	Single / not married	House / apartment	0.010032	-19046	-225	-4260.0	-2531	26.0	1	1	1	1	1	Laborers	1.0	2	2	MONDAY	9	0	0	Government	NaN	0.555912	0.729567	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.0	0.0	0.0	0.0	-815.0	0	0	0	0.0	0.0	0.0	0.0	0.0	0.0
3	100006	0	Cash loans	F	N	Y	0	135000.0	312682.5	29686.5	297000.0	Unaccompanied	Working	Secondary / secondary special	Civil marriage	House / apartment	0.008019	-19005	-3039	-9833.0	-2437	NaN	1	1	0	1	0	Laborers	2.0	2	2	WEDNESDAY	17	0	0	Business Entity Type 3	NaN	0.650442	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2.0	0.0	2.0	0.0	-617.0	1	0	0	NaN	NaN	NaN	NaN	NaN	NaN
4	100007	0	Cash loans	M	N	Y	0	121500.0	513000.0	21865.5	513000.0	Unaccompanied	Working	Secondary / secondary special	Single / not married	House / apartment	0.028663	-19932	-3038	-4311.0	-3458	NaN	1	1	0	1	0	Core staff	1.0	2	2	THURSDAY	11	1	1	Religion	NaN	0.322738	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.0	0.0	0.0	0.0	-1106.0	0	1	0	0.0	0.0	0.0	0.0	0.0	0.0
5	100008	0	Cash loans	M	N	Y	0	99000.0	490495.5	27517.5	454500.0	Spouse, partner	State servant	Secondary / secondary special	Married	House / apartment	0.035792	-16941	-1588	-4970.0	-477	NaN	1	1	1	1	1	Laborers	2.0	2	2	WEDNESDAY	16	0	0	Other	NaN	0.354225	0.621226	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.0	0.0	0.0	0.0	-2536.0	1	0	0	0.0	0.0	0.0	0.0	1.0	1.0
6	100009	0	Cash loans	F	Y	Y	1	171000.0	1560726.0	41301.0	1395000.0	Unaccompanied	Commercial associate	Higher education	Married	House / apartment	0.035792	-13778	-3130	-1213.0	-619	17.0	1	1	0	1	1	Accountants	3.0	2	2	SUNDAY	16	0	0	Business Entity Type 3	0.774761	0.724000	0.492060	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	0.0	1.0	0.0	-1562.0	0	1	1	0.0	0.0	0.0	1.0	1.0	2.0
7	100010	0	Cash loans	M	Y	Y	0	360000.0	1530000.0	42075.0	1530000.0	Unaccompanied	State servant	Higher education	Married	House / apartment	0.003122	-18850	-449	-4597.0	-2379	8.0	1	1	1	1	0	Managers	2.0	3	3	MONDAY	16	1	1	Other	NaN	0.714279	0.540654	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2.0	0.0	2.0	0.0	-1070.0	1	0	0	0.0	0.0	0.0	0.0	0.0	0.0
8	100011	0	Cash loans	F	N	Y	0	112500.0	1019610.0	33826.5	913500.0	Children	Pensioner	Secondary / secondary special	Married	House / apartment	0.018634	-20099	365243	-7427.0	-3514	NaN	1	0	0	1	0	NaN	2.0	2	2	WEDNESDAY	14	0	0	XNA	0.587334	0.205747	0.751724	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	0.0	1.0	0.0	0.0	1	0	0	0.0	0.0	0.0	0.0	0.0	1.0
9	100012	0	Revolving loans	M	N	Y	0	135000.0	405000.0	20250.0	405000.0	Unaccompanied	Working	Secondary / secondary special	Single / not married	House / apartment	0.019689	-14469	-2019	-14437.0	-3992	NaN	1	1	0	1	0	Laborers	1.0	2	2	THURSDAY	8	0	0	Electricity	NaN	0.746644	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2.0	0.0	2.0	0.0	-1673.0	0	0	0	NaN	NaN	NaN	NaN	NaN	NaN

Last rows

	SK_ID_CURR	TARGET	NAME_CONTRACT_TYPE	CODE_GENDER	FLAG_OWN_CAR	FLAG_OWN_REALTY	CNT_CHILDREN	AMT_INCOME_TOTAL	AMT_CREDIT	AMT_ANNUITY	AMT_GOODS_PRICE	NAME_TYPE_SUITE	NAME_INCOME_TYPE	NAME_EDUCATION_TYPE	NAME_FAMILY_STATUS	NAME_HOUSING_TYPE	REGION_POPULATION_RELATIVE	DAYS_BIRTH	DAYS_EMPLOYED	DAYS_REGISTRATION	DAYS_ID_PUBLISH	OWN_CAR_AGE	FLAG_MOBIL	FLAG_EMP_PHONE	FLAG_WORK_PHONE	FLAG_CONT_MOBILE	FLAG_PHONE	OCCUPATION_TYPE	CNT_FAM_MEMBERS	REGION_RATING_CLIENT	REGION_RATING_CLIENT_W_CITY	WEEKDAY_APPR_PROCESS_START	HOUR_APPR_PROCESS_START	REG_CITY_NOT_WORK_CITY	LIVE_CITY_NOT_WORK_CITY	ORGANIZATION_TYPE	EXT_SOURCE_1	EXT_SOURCE_2	EXT_SOURCE_3	APARTMENTS_AVG	BASEMENTAREA_AVG	YEARS_BEGINEXPLUATATION_AVG	YEARS_BUILD_AVG	COMMONAREA_AVG	ELEVATORS_AVG	ENTRANCES_AVG	FLOORSMAX_AVG	FLOORSMIN_AVG	LANDAREA_AVG	LIVINGAPARTMENTS_AVG	LIVINGAREA_AVG	NONLIVINGAPARTMENTS_AVG	NONLIVINGAREA_AVG	APARTMENTS_MODE	BASEMENTAREA_MODE	YEARS_BEGINEXPLUATATION_MODE	YEARS_BUILD_MODE	COMMONAREA_MODE	ELEVATORS_MODE	ENTRANCES_MODE	FLOORSMAX_MODE	FLOORSMIN_MODE	LANDAREA_MODE	LIVINGAPARTMENTS_MODE	LIVINGAREA_MODE	NONLIVINGAPARTMENTS_MODE	NONLIVINGAREA_MODE	APARTMENTS_MEDI	BASEMENTAREA_MEDI	YEARS_BEGINEXPLUATATION_MEDI	YEARS_BUILD_MEDI	COMMONAREA_MEDI	ELEVATORS_MEDI	ENTRANCES_MEDI	FLOORSMAX_MEDI	FLOORSMIN_MEDI	LANDAREA_MEDI	LIVINGAPARTMENTS_MEDI	LIVINGAREA_MEDI	NONLIVINGAPARTMENTS_MEDI	NONLIVINGAREA_MEDI	FONDKAPREMONT_MODE	HOUSETYPE_MODE	TOTALAREA_MODE	WALLSMATERIAL_MODE	EMERGENCYSTATE_MODE	OBS_30_CNT_SOCIAL_CIRCLE	DEF_30_CNT_SOCIAL_CIRCLE	OBS_60_CNT_SOCIAL_CIRCLE	DEF_60_CNT_SOCIAL_CIRCLE	DAYS_LAST_PHONE_CHANGE	FLAG_DOCUMENT_3	FLAG_DOCUMENT_8	FLAG_DOCUMENT_14	AMT_REQ_CREDIT_BUREAU_HOUR	AMT_REQ_CREDIT_BUREAU_DAY	AMT_REQ_CREDIT_BUREAU_WEEK	AMT_REQ_CREDIT_BUREAU_MON	AMT_REQ_CREDIT_BUREAU_QRT	AMT_REQ_CREDIT_BUREAU_YEAR
0	100002	1	Cash loans	M	N	Y	0	202500.0	406597.5	24700.5	351000.0	Unaccompanied	Working	Secondary / secondary special	Single / not married	House / apartment	0.018801	-9461	-637	-3648.0	-2120	NaN	1	1	0	1	1	Laborers	1.0	2	2	WEDNESDAY	10	0	0	Business Entity Type 3	0.083037	0.262949	0.139376	0.0247	0.0369	0.9722	0.6192	0.0143	0.00	0.0690	0.0833	0.1250	0.0369	0.0202	0.0190	0.0000	0.0000	0.0252	0.0383	0.9722	0.6341	0.0144	0.0000	0.0690	0.0833	0.1250	0.0377	0.022	0.0198	0.0	0.0	0.0250	0.0369	0.9722	0.6243	0.0144	0.00	0.0690	0.0833	0.1250	0.0375	0.0205	0.0193	0.0000	0.00	reg oper account	block of flats	0.0149	Stone, brick	No	2.0	2.0	2.0	2.0	-1134.0	1	0	0	0.0	0.0	0.0	0.0	0.0	1.0
1	100003	0	Cash loans	F	N	N	0	270000.0	1293502.5	35698.5	1129500.0	Family	State servant	Higher education	Married	House / apartment	0.003541	-16765	-1188	-1186.0	-291	NaN	1	1	0	1	1	Core staff	2.0	1	1	MONDAY	11	0	0	School	0.311267	0.622246	NaN	0.0959	0.0529	0.9851	0.7960	0.0605	0.08	0.0345	0.2917	0.3333	0.0130	0.0773	0.0549	0.0039	0.0098	0.0924	0.0538	0.9851	0.8040	0.0497	0.0806	0.0345	0.2917	0.3333	0.0128	0.079	0.0554	0.0	0.0	0.0968	0.0529	0.9851	0.7987	0.0608	0.08	0.0345	0.2917	0.3333	0.0132	0.0787	0.0558	0.0039	0.01	reg oper account	block of flats	0.0714	Block	No	1.0	0.0	1.0	0.0	-828.0	1	0	0	0.0	0.0	0.0	0.0	0.0	0.0
2	100004	0	Revolving loans	M	Y	Y	0	67500.0	135000.0	6750.0	135000.0	Unaccompanied	Working	Secondary / secondary special	Single / not married	House / apartment	0.010032	-19046	-225	-4260.0	-2531	26.0	1	1	1	1	1	Laborers	1.0	2	2	MONDAY	9	0	0	Government	NaN	0.555912	0.729567	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.0	0.0	0.0	0.0	-815.0	0	0	0	0.0	0.0	0.0	0.0	0.0	0.0
3	100006	0	Cash loans	F	N	Y	0	135000.0	312682.5	29686.5	297000.0	Unaccompanied	Working	Secondary / secondary special	Civil marriage	House / apartment	0.008019	-19005	-3039	-9833.0	-2437	NaN	1	1	0	1	0	Laborers	2.0	2	2	WEDNESDAY	17	0	0	Business Entity Type 3	NaN	0.650442	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2.0	0.0	2.0	0.0	-617.0	1	0	0	NaN	NaN	NaN	NaN	NaN	NaN
4	100007	0	Cash loans	M	N	Y	0	121500.0	513000.0	21865.5	513000.0	Unaccompanied	Working	Secondary / secondary special	Single / not married	House / apartment	0.028663	-19932	-3038	-4311.0	-3458	NaN	1	1	0	1	0	Core staff	1.0	2	2	THURSDAY	11	1	1	Religion	NaN	0.322738	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.0	0.0	0.0	0.0	-1106.0	0	1	0	0.0	0.0	0.0	0.0	0.0	0.0
5	100008	0	Cash loans	M	N	Y	0	99000.0	490495.5	27517.5	454500.0	Spouse, partner	State servant	Secondary / secondary special	Married	House / apartment	0.035792	-16941	-1588	-4970.0	-477	NaN	1	1	1	1	1	Laborers	2.0	2	2	WEDNESDAY	16	0	0	Other	NaN	0.354225	0.621226	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.0	0.0	0.0	0.0	-2536.0	1	0	0	0.0	0.0	0.0	0.0	1.0	1.0
6	100009	0	Cash loans	F	Y	Y	1	171000.0	1560726.0	41301.0	1395000.0	Unaccompanied	Commercial associate	Higher education	Married	House / apartment	0.035792	-13778	-3130	-1213.0	-619	17.0	1	1	0	1	1	Accountants	3.0	2	2	SUNDAY	16	0	0	Business Entity Type 3	0.774761	0.724000	0.492060	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	0.0	1.0	0.0	-1562.0	0	1	1	0.0	0.0	0.0	1.0	1.0	2.0
7	100010	0	Cash loans	M	Y	Y	0	360000.0	1530000.0	42075.0	1530000.0	Unaccompanied	State servant	Higher education	Married	House / apartment	0.003122	-18850	-449	-4597.0	-2379	8.0	1	1	1	1	0	Managers	2.0	3	3	MONDAY	16	1	1	Other	NaN	0.714279	0.540654	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2.0	0.0	2.0	0.0	-1070.0	1	0	0	0.0	0.0	0.0	0.0	0.0	0.0
8	100011	0	Cash loans	F	N	Y	0	112500.0	1019610.0	33826.5	913500.0	Children	Pensioner	Secondary / secondary special	Married	House / apartment	0.018634	-20099	365243	-7427.0	-3514	NaN	1	0	0	1	0	NaN	2.0	2	2	WEDNESDAY	14	0	0	XNA	0.587334	0.205747	0.751724	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	0.0	1.0	0.0	0.0	1	0	0	0.0	0.0	0.0	0.0	0.0	1.0
9	100012	0	Revolving loans	M	N	Y	0	135000.0	405000.0	20250.0	405000.0	Unaccompanied	Working	Secondary / secondary special	Single / not married	House / apartment	0.019689	-14469	-2019	-14437.0	-3992	NaN	1	1	0	1	0	Laborers	1.0	2	2	THURSDAY	8	0	0	Electricity	NaN	0.746644	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2.0	0.0	2.0	0.0	-1673.0	0	0	0	NaN	NaN	NaN	NaN	NaN	NaN

Overview

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Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category